AIS Research Insights

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New

AI Processed Human Approved

How can digital platforms help city leaders coordinate local experiments and adapt policies for long-term sustainability?

S.-V. Rehm, S. McLoughlin, G. Maccani

COPING WITH THE DYNAMICS OF URBAN SUSTAINABILITY: POSITIONING URBAN EXPERIMENTATION PLATFORMS AS TOOLS FOR POLICY MAKING

2021

Key findings

Urban experimentation platforms act as vital socio-technical bridges that align municipal policy-making, business ecosystems, and grassroots innovation.
A policy structure diagram illustrates key dynamic feedback loops where data and digital services directly inform and adapt local policy interventions.
Digital capabilities such as urban data observatories, open APIs, and challenge management portals empower collective intelligence and sustained civic engagement.

What it means for you

CIO / IT Executive: Allocate Q3 budget to architect an open API gateway and a centralized urban data observatory that connects municipal databases with external innovation platforms.
IT Manager: Draft technical requirements for a digital challenge management portal to ingest grassroots sensor data and track civic pilot projects.
Business Strategist: Schedule a meeting with local startup incubators and civic tech leaders to co-design a framework for integrating commercial solutions into municipal sustainability pilots.
Researcher: Map out the specific feedback loops between grassroots civic innovations and municipal policy outcomes using the study's System Dynamics approach as a baseline.
Policymaker: Draft a mandatory review checkpoint in the upcoming sustainability policy cycle that requires incorporating real-time data feeds from local urban experimentation platforms.

Digital Platform, Urban Experimentation, Urban Governance, System Dynamics, Urban Sustainability, Collective Intelligence

New

AI Processed Human Approved

How do combinations of different tools and routines help partner companies coordinate when developing new products?

Sven-V. Rehm, Lakshmi Goel

Composite Boundary Objects In Inter-Organizational Innovation Activities

2013

Key findings

Demonstrates that coordination across organizational boundaries is rarely driven by single, isolated tools, but rather through combinations of artifacts and routines termed composite boundary objects (CBOs).
Shows that effective collaboration emerges from the combined interplay of material objects (such as prototypes and central IT platforms), abstract concepts (such as shared product visions), and informal work routines.
Finds that cross-organizational coordination can emerge organically through everyday interactions, even when such coordination was not deliberately planned in advance.
Reveals that composite boundary objects are temporary and evolve across project milestones, requiring managers to support flexible environments of communication rather than focusing on standalone software applications.

What it means for you

CIO / IT Executive: Stop investing in standalone software silos and schedule a meeting with cross-company project leads on Monday morning to audit how your central IT platforms, shared physical prototypes, and communication routines are currently integrated to support external partners.
IT Manager: On Monday morning, map out the digital tools and informal communication channels your team uses with external partners, and set up a shared digital workspace that links these tools directly to ongoing physical prototyping milestones.
Business Strategist: On Monday morning, draft a flexible collaboration framework for your new product development project that combines shared product visions with routine check-ins, rather than relying on rigid, pre-planned coordination structures.
Researcher: On Monday morning, design a qualitative study protocol to trace how digital platforms, physical prototypes, and informal routines co-evolve across specific milestones in inter-organizational innovation projects.
Policymaker: On Monday morning, revise your innovation grant evaluation criteria to reward collaborative consortia that demonstrate flexible, multi-layered coordination mechanisms—such as combined digital and material artifact routines—rather than funding isolated software tools.

boundary objects, composite boundary objects, inter-organizational innovation, new product development, knowledge management, collaboration

New

AI Processed Human Approved

How can networked businesses quickly and cost-effectively integrate IT systems to support collaborative planning?

Sven-Volker Rehm

Architectural Design for Service-Supported Collaborative Work in Extended Enterprises

Americas Conference on Information Systems (AMCIS) · 2009

Key findings

A model-driven integration platform enables collaborative business applications to be built from reusable service components without modifying core internal systems.
Representing services as database models rather than custom software code drastically simplifies workflow modification and inter-firm data mapping.
A pilot implementation in a manufacturing network demonstrated that onboarding and integration time per partner could be reduced from four weeks to just a few days.
Shared service repositories allow networks of small and medium-sized enterprises to achieve significant economies of scale and extend enterprise planning capabilities to partners without advanced software.

What it means for you

CIO / IT Executive: Initiate an audit of all current custom point-to-point supply chain integrations and direct your architecture team to evaluate adopting a model-driven service platform to replace them.
IT Manager: Catalog your team's existing workflow and data integration tasks with external partners to identify which processes can be standardized into reusable database-backed service components.
Business Strategist: Draft a pilot project proposal to test a shared service repository with two key external manufacturing partners to evaluate reductions in onboarding time.
Researcher: Design a study to measure the exact time-to-onboard and transaction cost differentials between database-modeled services and traditional custom-code integrations in multi-firm networks.
Policymaker: Draft a grant funding framework that subsidizes shared service repositories and model-driven integration platforms specifically for small and medium-sized enterprise manufacturing networks.

Service-Oriented Architecture, Extended Enterprise, Enterprise Architecture, Enterprise Resource Planning, Business Process Modeling, Collaborative Networks

New

AI Processed Human Approved

How do remote teams collaborate and make complex decisions inside 3D virtual environments?

Lakshmi Goel, Sven-Volker Rehm

How teams complete tasks in virtual worlds

Americas Conference on Information Systems (AMCIS) · 2017

Key findings

Teams spend an extensive initial phase engaging in spatial and social sense-making rather than adopting an immediate task stance.
Progress occurs through multiple internal disruptions driven by hands-on tinkering rather than a single midpoint turnaround.
Virtual 3D objects serve as critical anchors that help members point, align perspectives, and reconcile individual viewpoints into shared team models.
Teams do not enter a second period of inertia, but rather cycle continuously through adjustments until reaching alignment.

What it means for you

CIO / IT Executive: Procure and provision enterprise-grade 3D virtual workspace software featuring interactive digital objects to serve as collaborative anchors for distributed teams.
IT Manager: Allocate the first 15 minutes of Monday's virtual team meeting to unguided spatial exploration and hands-on tinkering with the digital project board rather than jumping straight into the agenda.
Business Strategist: Restructure project timelines to eliminate expectations of a single midpoint review, replacing them with a framework that budgets time for continuous, iterative adjustments.
Researcher: Design a longitudinal study to observe how distributed teams utilize specific 3D visual anchors to reconcile divergent mental models over time.
Policymaker: Draft procurement standards for digital collaboration tools that mandate support for interactive 3D modeling and shared spatial environments to enhance remote worker accessibility and alignment.

Punctuated equilibrium, Boundary objects, Mental models, virtual worlds, team work, decision-making

New

AI Processed Human Approved

How can teams across an organization collaboratively map and visualize their business ecosystem to make better decisions?

Anne Faber, Adrian Hernandez-Mendez, Sven-Volker Rehm, Florian Matthes

Visualizing Business Ecosystems: Applying a Collaborative Modelling Process in Two Case Studies

2018

Key findings

Validated a six-step collaborative modeling process consisting of scoping, model instantiation, data collection, visualization, feedback adaptation, and storytelling.
Identified four critical collaboration roles that drive modeling success: the gatekeeper, facilitator, modeler, and recorder.
Discovered that ecosystem models evolve primarily at the attribute level rather than the entity level once visualization views are established.
Demonstrated that providing early, interactive visual layouts is vital to keeping stakeholders motivated during tedious data collection phases.
Showed that participants' prior modeling familiarity significantly affects progress, underscoring the need for hands-on preparatory training.

What it means for you

CIO / IT Executive: Procure and provision an agile, collaborative visualization software framework to support multi-stakeholder ecosystem mapping sessions this quarter.
IT Manager: Assign team members to specific collaboration roles—specifically gatekeeper, facilitator, modeler, and recorder—ahead of Monday's stakeholder workshop.
Business Strategist: Design an interactive, early visual layout of your target market ecosystem to present on Monday to maintain stakeholder engagement during data collection.
Researcher: Investigate how ecosystem models evolve specifically at the attribute level rather than the entity level during longitudinal case studies.
Policymaker: Develop hands-on preparatory training modules focused on modeling familiarity to better equip regional industry participants for collaborative workshops.

Business Ecosystem, Collaborative Modelling, Information Visualization, Action Research, Case Studies, Knowledge Management

New

AI Processed Human Approved

What different types of business ecosystems exist and how do they connect with one another?

Anne Faber, Maximilian Riemhofer, Sven-Volker Rehm, Gloria Bondel

A Systematic Mapping Study on Business Ecosystem Types

Americas Conference on Information Systems (AMCIS) · 2019

Key findings

Identifies 12 distinct business ecosystem types across academic literature, including platform, innovation, knowledge, software, IoT, and entrepreneurial ecosystems.
Maps ecosystems across two primary viewpoints: an organizational perspective centered on the enterprise and a product or service perspective centered on core value creation.
Highlights innovation ecosystems and platform business ecosystems as the most prominently discussed forms in literature.
Reveals that specialized types, such as IoT and customer-centric ecosystems, operate at the intersections of platform, knowledge, and innovation domains.
Demonstrates that software ecosystems uniquely bridge both organizational and product perspectives depending on their focus.

What it means for you

CIO / IT Executive: Review your current technology architecture on Monday morning to identify whether your software initiatives operate purely from an organizational or product perspective, and explicitly map them to one of the 12 recognized ecosystem types to align your IT investments with your enterprise's core value creation.
IT Manager: Audit your active platform and IoT projects on Monday morning by checking if they effectively bridge knowledge, innovation, and platform domains as outlined in the literature taxonomy, and flag any isolated technical silos for integration.
Business Strategist: Pull your strategic partnership portfolio on Monday morning and categorize each external alliance using the study's distinction between organization-centric and product-centric ecosystem types to identify gaps in your collaborative networks.
Researcher: Cross-reference your current literature review matrix on Monday morning against the 12 identified business ecosystem types to ensure your scope accounts for intersections between specialized domains like IoT and customer-centric ecosystems.
Policymaker: Examine your regional economic development grants on Monday morning to verify whether funding criteria adequately distinguish between broad innovation ecosystems and narrower platform or software ecosystems, ensuring targeted support for local tech clusters.

business ecosystem, innovation ecosystem, platform ecosystem, digital business ecosystem, systematic mapping study, software ecosystem

New

AI Processed Human Approved

What stops carmakers and software developers from creating shared data platforms, and what pushes them forward?

Gloria Bondel, Sven-Volker Rehm, Florian Matthes

JUST LINKING THE DOTS? BARRIERS AND DRIVERS TO CREATING VALUE FROM APPLICATION PROGRAMMING INTERFACES

2020

Key findings

External software developers drive early data access through workarounds like diagnostic hardware dongles and sustained pressure on carmakers.
Vehicle manufacturers implement APIs largely due to regulatory and standardization pressures rather than voluntary ecosystem growth, while maintaining tight gatekeeping.
The absence of proven commercial value propositions and fears of legal liability significantly delay manufacturer participation in open data sharing.
Intense competition over platform ownership and vehicle operating system control prevents manufacturers from standardizing on a common platform.
Emerging mobility trends, particularly autonomous driving, create future expectations that incentivize gradual steps toward open API ecosystems.

What it means for you

CIO / IT Executive: Initiate a legal risk-assessment workshop with compliance and legal counsel to draft clear liability frameworks for third-party API data sharing, removing internal roadblocks to manufacturer participation.
IT Manager: Audit all current vehicle diagnostic APIs and technical boundary resources to ensure they meet existing regulatory standards while safely accommodating third-party developer workarounds.
Business Strategist: Schedule a stakeholder alignment meeting to model a low-risk, shared-value commercial pilot focusing on autonomous driving data use cases, bypassing platform ownership deadlocks.
Researcher: Design a comparative interview study tracking how external software developers leverage diagnostic hardware dongles to pressure incumbent automakers into data access.
Policymaker: Draft standardized data-sharing guidelines that reduce legal liability fears for automotive manufacturers while mandating fair API access for third-party mobility start-ups.

Application Programming Interfaces, Boundary Resources, Digital Platforms, Automotive Industry, Connected Vehicles, Business Ecosystems

New

AI Processed Human Approved

How can digital experimentation platforms help city leaders make better, more adaptive urban sustainability policies?

Sven Volker Rehm, Shane McLoughlin, Brian Donnellan

HOW TO COPE WITH THE DYNAMICS OF URBAN SUSTAINABILITY: URBAN EXPERIMENTATION PLATFORMS AS TOOLS FOR ADAPTIVE POLICY-MAKING

2022

Key findings

Urban experimentation platforms function both as vehicles for implementing policy and as essential instruments for adaptive, feedback-driven policymaking.
Municipal decision-makers currently demonstrate low awareness of platform data, largely using platforms to broadcast priorities rather than using trial results to update policy.
Establishing structured feedback loops between urban business ecosystems, city authorities, and digital platforms substantially improves collaborative problem-solving and long-term sustainability.

What it means for you

CIO / IT Executive: Audit current urban data platforms to ensure they include incoming feedback channels from local experimentation trials, rather than functioning solely as one-way broadcast tools.
IT Manager: Configure dashboard alerts to aggregate and flag real-time stakeholder feedback and usage metrics from ongoing urban sustainability pilots.
Business Strategist: Initiate a meeting with municipal authorities and local business ecosystem partners to design a recurring framework for collaborative problem-solving using platform data.
Researcher: Apply system dynamics modeling to map the existing stakeholder feedback loops within your city's active urban experimentation platforms.
Policymaker: Review the latest data reports from active local sustainability trials and draft a plan to update an existing municipal policy based on the trial results.

Urban Sustainability, Urban Experimentation Platforms, Digital Platforms, Urban Governance, System Dynamics, Case Study

New

AI Processed Human Approved

What causes organizational inertia during digital transformation, and how does it block successful change?

Thomas Haskamp, Christian Dremel, Carolin Marx, Falk Uebernickel

Understanding Inertia in Digital Transformation: A Literature Review and Multilevel Research Framework

International Conference on Information Systems (ICIS) · 2021

Key findings

Conceptualizes inertia through five key attributes: paradoxical duality (vital for efficiency yet resistant to change), rigidity of social/material entities, relational character, time-dependency, and misalignment with the environment.
Identifies nine distinct dimensions of inertia spanning individual (behavioral, cognitive, affective), organizational (structural, cultural, socio-technical, political, economic), and industry levels.
Maps 12 antecedents—ranging from individual cognitive flexibility to organizational routines, legacy IT, culture, and external uncertainty—that give rise to inertia.
Outlines 12 critical consequences of inertia, including active employee resistance, biased management decision-making, project failures, compromised agility, and failure to renew business models.
Pinpoints 15 moderating factors, such as dynamic capabilities, agility, absorptive capacity, and managerial cognition, that influence how inertia translates into operational impacts.

What it means for you

CIO / IT Executive: Audit your portfolio for socio-technical legacy IT misalignments by scheduling a joint review with department heads to identify legacy systems anchoring obsolete business routines.
IT Manager: Map your team's current project workflows against the five inertia attributes to pinpoint where cognitive and behavioral rigidity is slowing down daily software deployment.
Business Strategist: Review the 12 documented inertia antecedents against your current transformation roadmap to identify which cultural and structural barriers threaten your upcoming business model renewal.
Researcher: Formulate a new empirical study focusing on the interactions between individual-level cognitive inertia and organizational-level structural inertia during enterprise cloud migrations.
Policymaker: Draft guidelines for state-backed digital grants that require organizations to explicitly account for socio-technical and cultural inertia mitigation strategies before receiving funding.

digital transformation, organizational inertia, socio-technical inertia, change resistance, dynamic capabilities, literature review

AI Processed Human Approved

How do on-screen interruptions affect task performance on mobile devices compared to desktop computers?

Lior Fink, Esti Baranes, Naama Ilany-Tzur

Mobile use in an age of interruption: Implications of capacity and structural interference for mobile users

2025

Key findings

Mobile users suffer higher resumption costs, taking significantly longer to resume a primary task after an interruption compared to PC users.
Mobile users experience lower task-switching costs because they store less primary-task information in working memory, making them less vulnerable to cognitive conflict during interrupting tasks.
PC users face greater structural interference and longer completion times on interrupting tasks that share cognitive mechanisms with the primary task.
Application developers should adapt mobile interfaces by modularizing complex workflows into smaller, independent subtasks to accommodate mobile attention limitations.

What it means for you

CIO / IT Executive: On Monday morning, initiate a review of the current mobile application development roadmap, prioritizing projects that involve complex workflows to identify opportunities for modularization into smaller, independent subtasks in the next development cycle.
IT Manager: On Monday morning, schedule a brief meeting with your mobile development team to discuss the research findings on higher resumption costs for mobile users and explore practical strategies for simplifying user interfaces and reducing cognitive load on mobile applications they manage.
Business Strategist: On Monday morning, analyze customer feedback and usage data for core mobile applications to identify specific complex workflows that are likely causing high resumption costs and explore opportunities to redesign these for improved user efficiency.
Researcher: On Monday morning, begin drafting a follow-up experiment proposal that specifically quantifies the impact of pre-defined 'modularized subtask' interfaces on mobile resumption costs compared to current complex workflows, using the findings from this study as a baseline.
Policymaker: On Monday morning, draft a memo to relevant committees and agencies proposing the inclusion of 'mobile interface design standards' that encourage modularization of complex tasks to improve digital accessibility and productivity for mobile users.

Mobile Device, Interruption, Attention, Capacity Interference, Structural Interference, Task Performance

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 do TikTok users respond when young adults share their struggles with depression?

Gordon Amidu

The Impact of Cyberbullying on Help-Seeking Among Depressed Young adults in the United States

2025

Key findings

Non-cyberbullying comments significantly outnumbered cyberbullying comments, accounting for 92.2% of overall engagement compared to 7.8% cyberbullying interactions.
Supportive responses were the most common interaction style (53.51%), followed by harmful (17.68%), dismissive (15.91%), sarcastic (8.83%), peer invalidation (3.42%), and blaming (0.65%) comments.
Sentiment analysis revealed that responses to depression-related content were predominantly neutral, reflecting cautious and non-judgmental user engagement.
Topic modeling identified five primary thematic areas in user discussions: Emotional Vulnerability, Identity Struggles, Social Connection, Negative Emotions, and Emotional Expression.

What it means for you

CIO / IT Executive: On Monday morning, direct your cybersecurity team to review existing platform moderation tools and policies for social media platforms commonly used by young adults, with a specific focus on identifying potential enhancements to detect and flag harmful comment patterns identified in the research (e.g., dismissive, sarcastic, peer invalidation).
IT Manager: On Monday morning, initiate a review of our internal IT support resources and documentation related to online safety and responsible social media use, ensuring it includes guidance on identifying and reporting cyberbullying, and consider adding specific examples of the types of harmful comments found in the research.
Business Strategist: On Monday morning, task your market research team to analyze the brand's current social media engagement strategy on platforms like TikTok, specifically looking for opportunities to amplify supportive and positive content in response to mental health disclosures, and to identify potential risks associated with negative comment trends.
Researcher: On Monday morning, begin planning your next research project by drafting a proposal to replicate this study's methodology on other emerging social media platforms or with different demographic groups to broaden the understanding of cyberbullying's impact on help-seeking behavior.
Policymaker: On Monday morning, schedule a meeting with your legislative aides to begin drafting policy recommendations that encourage social media platforms to implement more robust content moderation systems specifically designed to identify and mitigate cyberbullying that hinders vulnerable individuals from seeking help.

cyberbullying, mental health, TikTok, depression, social media harassment, help-seeking

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

What drives digital gullibility, and how can systems be designed to help users critically evaluate online information?

Margeret Hall, Christian Haas

A Research Agenda to Understand Drivers of Digital Gullibility

International Conference on Information Systems (ICIS) · 2022

Key findings

Frames digital gullibility as a key antecedent to maladaptive online behaviors rather than focusing solely on misinformation output.
Integrates socio-technical system principles with concepts like context collapse and network externalities to explain persistent online gullibility.
Formulates ten research propositions across three gaps: information context, individual seeking behavior, and realized behavior.
Provides actionable guidance for designing user-centric systems that enhance epistemic vigilance and reduce information verification costs.

What it means for you

CIO / IT Executive: On Monday morning, initiate a cross-departmental working group with representatives from Security, User Experience, and Training to review the research agenda's propositions, specifically focusing on how to integrate 'epistemic vigilance' enhancement into the next IT security awareness training module, prioritizing the 'information context' gap.
IT Manager: On Monday morning, schedule a 30-minute review session with your team to discuss the concept of 'context collapse' as presented in the research and brainstorm one specific system design tweak (e.g., adding a 'source credibility' indicator to internal dashboards) that could reduce information verification costs for your users, to be piloted within the week.
Business Strategist: On Monday morning, draft a one-page executive summary for your leadership team that translates the research's core finding on 'digital gullibility as an antecedent to maladaptive online behaviors' into a business risk, proposing a brief for exploring how to quantify the cost of digital gullibility within your organization's operations.
Researcher: On Monday morning, begin a literature review focused on the 'individual seeking behavior' gap outlined in the research, specifically searching for empirical studies that measure user-reported 'epistemic vigilance' in different online environments to refine your next research question.
Policymaker: On Monday morning, draft an inquiry to relevant government agencies or industry bodies requesting current data on the prevalence and economic impact of 'digital scams' and 'phishing' within your jurisdiction, framing the request around understanding 'digital gullibility' as a root cause.

Digital gullibility, maladaptive outcomes, context collapse, network externalities, epistemic vigilance, socio-technical systems

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 visual tools help organizations understand and manage complex smart city mobility platforms?

Sven-Volker Rehm, Anne Faber, Lakshmi Goel

Visualizing Platform Hubs of Smart City Mobility Business Ecosystems

International Conference on Information Systems (ICIS) · 2017

Key findings

Implemented five distinct visualization techniques (Force-directed, Tree Map, Matrix, Radial Network, and Modified Ego-Network layouts) within a software prototype to match diverse stakeholder decision-making needs.
Demonstrated how macro-level visual analytics can uncover key industry players, platform overlaps, missing service niches, and dominant inter-firm relationships.
Conceptualized a framework showing how tailored ecosystem visualizations can stimulate vital knowledge flows across policy governance boards, commercial firms, and smart city citizen communities.

What it means for you

CIO / IT Executive: On Monday morning, review the 'business ecosystem explorer' software prototype documentation and identify which of the five visualization techniques (Force-directed, Tree Map, Matrix, Radial Network, Modified Ego-Network) are most technically feasible for immediate integration into existing smart city data infrastructure.
IT Manager: On Monday morning, schedule a brief technical assessment meeting with your team to evaluate the infrastructure requirements and potential integration points for a pilot implementation of one or two of the presented visualization techniques from the 'business ecosystem explorer' prototype.
Business Strategist: On Monday morning, initiate a discussion with your cross-functional team to brainstorm specific strategic questions about our smart city mobility ecosystem that could be answered by analyzing platform overlaps, missing service niches, and dominant inter-firm relationships using the described macro-level visual analytics.
Researcher: On Monday morning, analyze the research paper's findings on how tailored ecosystem visualizations stimulate knowledge flows and identify which specific visualization technique and corresponding stakeholder group (policy governance, commercial firms, citizen communities) offers the most promising avenue for a follow-up research experiment.
Policymaker: On Monday morning, identify a key policy governance challenge related to smart city mobility coordination and consider how a macro-level visualization of platform hubs, as described in the research, could provide actionable insights to address this challenge.

Digital platform, business ecosystem, smart city, visualization, knowledge flow

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

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

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