AIS Research Insights

Browse the library 34 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

AI Processed Human Approved

What forms of cyberbullying do adolescents experience in gamified TikTok trends, and how do they differ by gender?

Gordon Amidu

The Impact of Gamified Cyberbullying Trends on Adolescent Mental Health on TikTok in the U.S.

2025

Key findings

Non-cyberbullying comments comprised over 96% of all interactions, demonstrating the impact of automated platform moderation and bystander intervention.
Sexualization emerged as the predominant cyberbullying tactic, accounting for 92.46% of male-directed cyberbullying and 89.19% of female-directed cyberbullying.
Gendered patterns were prominent in topic modeling: male content elicited performance-based roasts, whereas female content attracted appearance-focused rating commentary.
Sentiment analysis showed that female adolescents received proportionally more neutral audience responses and fewer negative reactions than male peers.

What it means for you

CIO / IT Executive: Initiate a review of the current content moderation algorithms and their effectiveness in identifying and flagging subtle forms of gamified cyberbullying, particularly sexualization and appearance-focused commentary, as outlined in the research. Schedule a follow-up meeting with the AI/ML team by Wednesday to discuss potential enhancements based on these findings.
IT Manager: Begin analyzing the platform's reporting mechanisms. Identify any user-facing features that might be inadvertently hindering adolescents from reporting gamified cyberbullying by making it appear 'playful'. Prepare a brief report by end of day Monday on potential UI/UX improvements for reporting tools, focusing on clarity and ease of use.
Business Strategist: Develop a preliminary risk assessment framework for new gamified campaign launches on TikTok. This framework should explicitly incorporate potential negative externalities like gamified cyberbullying and its gendered manifestations, as identified in the research, and assess how these risks might impact brand reputation and user engagement.
Researcher: Begin designing a follow-up study protocol. Focus on how to specifically capture and analyze 'playful' or gamified cyberbullying that might evade current detection methods, using the research findings on sexualization and appearance-based commentary as key indicators. Prioritize developing an analytical framework that distinguishes between genuine 'roasts' and harmful cyberbullying.
Policymaker: Draft a policy brief for internal review that outlines the need for updated platform guidelines. This brief should specifically address the challenge of gamified cyberbullying on platforms like TikTok, referencing the research's findings on sexualization and gendered patterns, and proposing that platforms implement clearer definitions and more robust enforcement mechanisms for these evolving forms of online harassment.

cyberbullying, gamification-trolling, TikTok, gender, adolescent online behavior, social media

AI Processed Human Approved

How can universities better organize themselves to adapt and deliver effective online learning?

Indriani Noor Hapsari, Dana Indra Sensuse, Harry Budi Santoso, Indra Budi, Ryan Randy Suryono, Kautsarina

Improving Self-Organization Capability in e-Learning using Soft System Methodology: A Case from Indonesia

International Conference on Information Systems (ICIS) · 2024

Key findings

Identified four core dimensions influencing self-organization in higher education: strategic planning, personnel development, learning resource management, and IT capability.
Formulated seven actionable interventions, including establishing clear multi-year strategies, promoting open dialogue across faculties, visualizing workload allocations, and implementing collaborative feedback mechanisms for course design.
Highlighted the vital roles Information Systems play as enablers for group decision-making, performance tracking, knowledge sharing, and managing system dependencies.

What it means for you

CIO / IT Executive: On Monday morning, initiate a review of existing IT infrastructure and systems specifically identifying which ones are currently siloed and propose an initial phased approach (e.g., Phase 1: Integration of student information system with the learning management system) for breaking down these silos, with a preliminary timeline and resource estimate.
IT Manager: On Monday morning, schedule a 30-minute check-in with a representative from the academic affairs department to discuss how existing IT systems can better support collaborative feedback mechanisms for course design, identifying one specific tool or feature that could be enhanced or implemented in the next sprint.
Business Strategist: On Monday morning, draft a one-page outline for a multi-year e-learning strategy document, focusing on how to integrate the identified four core dimensions (strategic planning, personnel development, learning resource management, IT capability) into measurable objectives for the next academic year, and identify one key stakeholder group for initial feedback.
Researcher: On Monday morning, begin compiling a list of existing open-dialogue platforms or communication channels within the university and identify two specific instances where they could be leveraged to facilitate cross-faculty discussions on e-learning best practices or challenges.
Policymaker: On Monday morning, draft a memo to the academic senate proposing a pilot program for a collaborative feedback mechanism for course design, outlining the key benefits, the intended process, and requesting their endorsement to explore its feasibility further.

soft-system methodology, self-organization, higher education, e-learning, information system, Indonesia

AI Processed Human Approved

How do communities use social media to support mental health recovery during natural disasters?

Mohammad Ariful Islam, Julian Marx, Libo Liu, Ofir Turel

Digital Mental Health Resilience During Natural Disasters: A Scoping Review and Research Agenda

2025

Key findings

Identified seven key socio-technical themes describing how social media fosters mental health resilience across natural disaster phases.
Revealed that communities actively curate content and self-regulate online spaces to protect users from distress, misinformation, and trauma.
Demonstrated the importance of vulnerability-sensitive channels and cross-sector coordination among community groups, government agencies, and mental health providers.

What it means for you

CIO / IT Executive: On Monday morning, schedule a brief exploratory meeting with your innovation team to assess existing social media monitoring tools and identify potential enhancements for detecting and analyzing distress signals and misinformation during simulated disaster scenarios.
IT Manager: On Monday morning, review the current moderation policies for any public-facing community forums or social media channels managed by your organization, and identify specific criteria related to 'vulnerability-sensitive content' that could be integrated into moderation guidelines.
Business Strategist: On Monday morning, initiate a conversation with your communications and marketing teams to explore how your organization's social media presence could be adapted to proactively offer mental health resources or foster supportive community interactions, especially in light of potential regional disaster risks.
Researcher: On Monday morning, begin drafting a concise summary of the 'vulnerability-sensitive channels' and 'cross-sector coordination' findings from this review, identifying specific examples or hypothetical scenarios where these could be applied to digital mental health resilience research.
Policymaker: On Monday morning, draft a short memo to your relevant department heads, flagging the research finding on 'communities actively curate content and self-regulate online spaces' and suggesting a brief discussion on how public digital platforms could be better designed or supported to facilitate this self-regulation for mental health resilience during crises.

Social media, natural disasters, digital mental health resilience, community resilience, scoping review

AI Processed Human Approved

How can educators successfully use community partner projects to teach practical technology and project management skills?

Margeret Hall

Service Learning in Information Systems Education: Pedagogical Approaches to Support Experiential Learning and Higher-level Thinking

International Conference on Information Systems (ICIS) · 2018

Key findings

Integrating service learning into Information Systems classrooms increases student motivation and engagement by connecting technical tasks to pro-social community impacts.
Employing constructivist classroom management alongside Agile methodologies effectively supports higher-level thinking skills, including critical evaluation and self-reflection.
High team cohesion can be a double-edged sword, occasionally masking individual inefficiencies and inhibiting necessary exchanges with external stakeholders.
Assessing students on their execution of Agile project management processes rather than purely technical deliverables protects individual grading fairness and encourages risk-taking.

What it means for you

CIO / IT Executive: On Monday morning, initiate a pilot program to identify two to three non-profit organizations in our community that could benefit from IT support, and assign a dedicated internal IT liaison for each to manage the student engagement.
IT Manager: On Monday morning, schedule a 30-minute meeting with your team to brainstorm potential IT projects that could be beneficial for local non-profits, focusing on areas where student teams could realistically make an impact within a semester.
Business Strategist: On Monday morning, reach out to a local community foundation or non-profit umbrella organization to understand their most pressing IT needs and explore potential service learning partnerships for future student projects.
Researcher: On Monday morning, begin drafting a literature review section of your paper, specifically focusing on case studies of service learning in technical fields and the reported challenges and benefits of integrating Agile methodologies in such contexts.
Policymaker: On Monday morning, begin drafting a proposal for a new grant or funding initiative that encourages universities to partner with local non-profits for experiential learning opportunities in Information Systems, emphasizing the development of practical, community-focused IT skills.

Service Learning, IS Education, Constructivism, Bloom's Taxonomy, Experiential Learning

AI Processed Human Approved

How can collaborative software be designed so domain experts can configure it for their specific needs?

Sven-Volker Rehm, Thomas Reschenhofer, Klym Shumaiev

IS Design Principles for Empowering Domain Experts in Innovation: Findings From Three Case Studies

International Conference on Information Systems (ICIS) · 2014

Key findings

Identified key design principles for domain expert configurable software, including iterative modeling, content-context relation, information re-use, function re-use, and context alignment.
Highlighted the essential role of 'facilitators' as mediating agents who help bridge technical configuration mechanisms with business domain requirements.
Demonstrated that domain expert configuration provides a flexible, cost-effective method to align IT support with dynamic inter-organizational innovation processes.

What it means for you

CIO / IT Executive: On Monday morning, schedule a brief meeting with your innovation network leads to discuss the potential of 'domain expert configuration' for upcoming projects, specifically asking them to identify one current pain point related to rigid software that could be addressed by such a system.
IT Manager: On Monday morning, review your current internal documentation for any existing examples of 'facilitators' – individuals who successfully bridge technical and business needs – and plan a quick chat with one of them to understand their approach.
Business Strategist: On Monday morning, draft a one-page concept document outlining how a more flexible, domain expert-configurable information system could accelerate a specific strategic innovation initiative, focusing on the benefits of rapid adaptation to diverse partner needs.
Researcher: On Monday morning, identify three publicly available collaborative information systems (e.g., wikis, content management systems) that exhibit elements of 'content-context relation' or 'information re-use' and briefly document how they do so.
Policymaker: On Monday morning, review existing procurement guidelines for IT systems to identify any clauses that might hinder the adoption of flexible, configurable solutions, and consider proposing a pilot program to test the effectiveness of domain expert configuration for inter-organizational projects.

Domain expert configuration, design science, innovation networks, domain knowledge, design principles, case study

AI Processed Human Approved

What combinations of contract terms make IT outsourcing projects successful as technology changes over time?

Onkar S. Malgonde, Moez Farokhnia Hamedani, Sunil Mithas, Manish Agrawal, Kaushal Chari

How Do Technology Paradigms Influence Configurations of Contract Characteristics for Success of Inter-Organizational Outsourcing Projects, 1991–2009?

2026

Key findings

Configurations of contract characteristics associated with outsourcing success differ significantly across technology paradigms.
Three overarching configurational themes lead to success: Economic Imperative, Conservative Relational, and Conservative Imperative.
Over time, firms have placed an increasing emphasis on the relational component to manage contracting risk alongside formal contractual terms.

What it means for you

CIO / IT Executive: On Monday morning, convene your IT leadership team to review the five core contract features analyzed in this research and discuss how they might be re-weighted or re-configured for your current technology paradigm and outsourcing portfolio. Specifically, identify which features (e.g., scope definition, performance metrics, governance mechanisms) are most critical for upcoming or existing projects and how they align with 'Economic Imperative', 'Conservative Relational', or 'Conservative Imperative' themes.
IT Manager: On Monday morning, pull the contract documents for your most critical ongoing IT outsourcing project. Identify and list the specific clauses related to scope, performance metrics, payment terms, and dispute resolution. Then, for each clause, assess its 'formality' (highly specific and legalistic vs. more flexible and outcome-oriented) and 'relationality' (terms fostering collaboration and trust vs. purely transactional terms), noting potential areas for adjustment to better fit your project's technology paradigm.
Business Strategist: On Monday morning, identify the top 2-3 inter-organizational IT outsourcing projects that are currently critical to achieving your business objectives. For each of these projects, analyze whether the current contract characteristics lean more towards an 'Economic Imperative' (cost reduction focus), 'Conservative Relational' (balancing cost with strong partnership), or 'Conservative Imperative' (risk aversion through strict control). Then, evaluate if this alignment is still optimal given the project's technology and your evolving business strategy.
Researcher: On Monday morning, identify the primary technology paradigm (e.g., cloud computing, AI/ML, legacy systems) that is dominant in your current research focus on IT outsourcing. Then, cross-reference this with the three overarching configurational themes identified in the research ('Economic Imperative', 'Conservative Relational', and 'Conservative Imperative'). Begin outlining a framework for how you will specifically analyze the contract characteristics within that chosen paradigm to identify context-sensitive recipes for success.
Policymaker: On Monday morning, review existing government procurement guidelines for IT outsourcing contracts. Specifically, identify how flexible or rigid these guidelines are regarding the interplay of formal contractual terms and the emphasis on relational components. Consider proposing an amendment to encourage a more nuanced approach that allows for adaptable contract configurations based on the technology paradigm and the increasing importance of building trust and collaboration in outsourcing relationships.

contracting risk, equifinality, interorganizational projects, qualitative comparative analysis, technology outsourcing, set-theoretical approach

AI Processed Human Approved

How can organizations define and select performance indicators for collaborative business networks?

Montijn van de Ven, Paola Lara Machado, Banu Aysolmaz, Oktay Turetken

Managing Performance in Collaborative Networks: A Method for Defining Key Performance Indicators for Collaborative Business Models

Business & Information Systems Engineering · 2026

Key findings

Introduced a three-step method covering KPI specification, multi-criteria KPI selection, and attribute operationalization.
Differentiated KPI scopes into network, subnet, and actor levels to balance network alignment with individual flexibility.
Demonstrated practical utility through business scenarios including car navigation services, urban indoor farming, and sustainable households.

What it means for you

CIO / IT Executive: On Monday morning, initiate a pilot project to apply the three-step KPI definition method to one specific collaborative network your organization participates in, focusing on identifying and documenting initial network-level KPIs using your existing data infrastructure.
IT Manager: On Monday morning, schedule a working session with a key business stakeholder from a collaborative project to begin the 'KPI specification' step of the research method, focusing on articulating the desired outcomes for that specific collaboration.
Business Strategist: On Monday morning, review the research's findings on differentiating KPI scopes and draft a preliminary list of potential network, subnet, and actor-level KPIs for a newly forming collaborative initiative.
Researcher: On Monday morning, begin designing a case study to apply and further refine the proposed KPI definition method within a new collaborative business scenario, focusing on the 'multi-criteria KPI selection' and 'attribute operationalization' steps.
Policymaker: On Monday morning, identify a specific public-private collaborative initiative and begin exploring how the research's approach to KPI definition could be adapted to measure its network-wide alignment and individual actor contributions effectively.

Business models, Collaborative business models, Collaborative networks, Key performance indicators, Performance management, Design science research

AI Processed Human Approved

How can organizations identify the operational changes needed after redesigning their business model?

Paola Lara Machado, Montijn van de Ven, Banu Aysolmaz, Oktay Turetken, Jan vom Brocke

Navigating Business Model Redesign: The Compass Method for Identifying Changes to the Operating Model

Business & Information Systems Engineering · 2024

Key findings

Formulated and validated the Compass Method, a structured three-step framework using design cards to translate business model changes into concrete operating model adaptations.
Established prescriptive design objectives and solution knowledge bridging the research gap between business model innovation and operational business process management.
Demonstrated across multiple evaluations that the method enhances traceability, standardizes operational change planning, and facilitates alignment between business and technical stakeholders.

What it means for you

CIO / IT Executive: On Monday morning, review the executive summary of the Compass Method paper and identify which of the 'design objectives' and 'solution knowledge' areas align with current or planned IT infrastructure investments to support business model redesigns.
IT Manager: On Monday morning, pull up the 'operating model design cards' described in the paper and, referencing a recent business model change initiative, begin mapping existing IT processes and systems to these cards to identify potential operational gaps or inefficiencies.
Business Strategist: On Monday morning, dedicate two hours to familiarize yourself with the three steps of the Compass Method and prepare to facilitate a pilot session next week applying the method to a specific, recently redesigned business model component.
Researcher: On Monday morning, begin analyzing the empirical case study data presented in the paper, focusing on the specific metrics or indicators used to demonstrate the effectiveness of the Compass Method in enhancing traceability and standardizing operational change planning.
Policymaker: On Monday morning, read the 'problem' section of the research and consider how the described gap between business model redesign and operational implementation might be addressed by future organizational policy or standard operating procedures, potentially incorporating elements of structured change planning.

Business model, Operating model, Business process management, Organizational design, Process change, Design science research

AI Processed Human Approved

How do laws banning businesses from suppressing negative reviews affect online customer ratings?

Aida Sanatizadeh, Gordon Burtch, Yili Hong, Yuheng Hu

Can Regulation Restore Authenticity? Evidence from Policies Against Online Review Suppression

Information Systems Research · 2025

Key findings

Following the CRFA enactment, U.S. hotel reviews became systematically more negative in both star ratings and textual sentiment.
Reviews became significantly longer on average, indicating that consumers shared more detailed feedback once legal risks were mitigated.
Rating declines were most concentrated among less reputable hotels and those in highly competitive local markets, which previously suppressed negative reviews more aggressively.
The policy's effects were strongest among American reviewers and users with longer platform tenure.

What it means for you

CIO / IT Executive: On Monday morning, initiate a review of our internal policies and legal contracts to ensure no clauses inadvertently threaten or discourage customers from providing honest feedback on public review platforms.
IT Manager: On Monday morning, task your team with monitoring online review platforms for any patterns of review suppression tactics being used by our competitors, specifically looking for increases in negative reviews that are quickly removed or challenged.
Business Strategist: On Monday morning, analyze recent customer feedback data, particularly any negative reviews received in the last quarter, and assess if there are opportunities to engage with these customers to improve our offerings and address concerns openly.
Researcher: On Monday morning, identify and gather publicly available datasets on consumer review sentiment and volume for companies in sectors known for aggressive review suppression prior to recent regulatory changes, to replicate or extend the findings on the CRFA.
Policymaker: On Monday morning, schedule a meeting with your legislative staff to discuss potential avenues for expanding regulatory protections to cover other forms of consumer feedback, such as social media comments or product testimonials, building upon the success of the CRFA.

Consumer Review Fairness Act, Online Reviews, Review Suppression, Chilling Effect, Digital Platforms, Consumer Protection

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

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 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 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

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

Load More Showing 18 of 34