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New Email stress: Towards a new understanding of its causes and impacts
AI Processed Human Approved

How do sending and receiving emails shape employee stress and productivity?

Jean-François Stich
Email stress: Towards a new understanding of its causes and impacts
2025
Key findings
  • The paper proposes the Transactional Model of Email Stress (TMES), establishing that email stress is a dynamic process shaped by sender and receiver roles.
  • Sending emails generally triggers eustress, offering senders a sense of control, task delegation, and productivity.
  • Receiving emails primarily creates distress through incoming volume, constant interruptions, and emotional ambiguity in messages.
  • Targeted email training and explicit organizational communication norms can mitigate distress while preserving productivity benefits.
What it means for you
  • CIO / IT Executive: On Monday morning, initiate a discussion with your direct reports and heads of departments to explore piloting a specific email management training program for all employees, focusing on techniques that address both sender eustress and receiver distress, as outlined by the TMES model.
  • IT Manager: On Monday morning, review the current email client settings and identify opportunities to implement or enhance features that automatically categorize or filter incoming emails based on sender or keywords, thereby reducing receiver distress for your team.
  • Business Strategist: On Monday morning, draft a proposal for a new organizational communication norm that encourages concise and action-oriented email content from senders, aiming to maximize sender eustress by clearly delegating tasks and minimizing receiver distress caused by ambiguity.
  • Researcher: On Monday morning, begin drafting a research proposal to empirically test the TMES model by designing a study that measures sender eustress and receiver distress across different organizational contexts and email usage patterns.
  • Policymaker: On Monday morning, schedule a meeting with key stakeholders to discuss the development of an organizational policy that mandates specific email etiquette training, emphasizing balanced sender and receiver perspectives as informed by the TMES framework.
Email stress, Technostress, Overload, Hyperconnection, Eustress, Transactional model
WHEN ALGORITHMS DELEGATE TO HUMANS: EXPLORING HUMAN-ALGORITHM INTERACTION AT UBER
AI Processed Human Approved

How do algorithms delegate work to groups of humans on digital platforms?

Marta Stelmaszak, Mareike Möhlmann, Carsten Sørensen
WHEN ALGORITHMS DELEGATE TO HUMANS: EXPLORING HUMAN-ALGORITHM INTERACTION AT UBER
MIS Quarterly · 2024
Key findings
  • Conceptualizes distributed delegation as a collective, hybrid, and relational process where multiple algorithms work together while drawing on human data inputs.
  • Identifies three key mechanisms of algorithmic delegation in multi-agent settings: collective hybrid appraisal, collective hybrid distribution, and collective hybrid coordination.
  • Reveals that delegation functions along a continuum rather than as a complete, binary transfer of rights and responsibilities between algorithms and humans.
  • Demonstrates that human involvement—through trace data, choice data, and direct interventions during breakdowns—is necessary for algorithmic agency to operate.
What it means for you
  • CIO / IT Executive: On Monday morning, initiate a review of our current platform architecture to identify all instances of multi-agent algorithmic systems and assess their delegation models, specifically looking for 'distributed delegation' patterns to ensure human input is integrated effectively.
  • IT Manager: On Monday morning, schedule a technical deep-dive with your team focused on one specific algorithmic system that delegates to humans; analyze its current delegation logic and identify specific points where human trace data, choice data, or direct intervention are critical inputs, and document these dependencies.
  • Business Strategist: On Monday morning, begin a strategic assessment of our core business processes that rely on algorithmic delegation; map out the human touchpoints and decision points that are currently integrated, or could be integrated, within a 'distributed delegation' framework to enhance system resilience and adaptability.
  • Researcher: On Monday morning, draft a research proposal outlining a study to quantitatively measure the impact of 'distributed delegation' on system performance and user satisfaction in our specific domain, focusing on how varying levels of human input influence outcomes.
  • Policymaker: On Monday morning, convene a working group to examine existing regulations and internal policies related to algorithmic decision-making and human oversight; identify any gaps that need addressing to better accommodate 'distributed delegation' scenarios, ensuring clarity on accountability and human agency.
IS Delegation, Human-AI Interaction, Artificial Intelligence, Algorithms, Patents
Mobile use in an age of interruption: Implications of capacity and structural interference for mobile users
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
Cyberbullying in Times of School Shootings: Effects on Youth Mental Health in the U.S.
AI Processed Human Approved

How do online reactions and bullying differ for young males and females posting about school shootings?

Gordon Amidu
Cyberbullying in Times of School Shootings: Effects on Youth Mental Health in the U.S.
2025
Key findings
  • Non-cyberbullying comments occurred significantly more frequently than cyberbullying comments across posts from both male and female youth creators.
  • Emotional trauma responses were the predominant cyberbullying behavior, comprising 52.69% of harassment on male posts and 63.97% on female posts, while aggression, sarcasm, and blame occurred less than expected.
  • Topic modeling revealed gendered discussion dynamics, where male posts prompted political discourse and threat-focused debates, while female posts elicited supportive, emotionally processing, and healing-oriented conversations.
  • Sentiment analysis indicated that posts by young females received a higher proportion of neutral comments and fewer negative reactions compared to posts by young males.
What it means for you
  • CIO / IT Executive: On Monday morning, initiate a review of existing content moderation policies and technologies to ensure they are sufficiently equipped to detect and flag 'emotional trauma responses' as a primary form of cyberbullying, particularly in the context of sensitive national crises, and prioritize implementing enhanced AI-driven sentiment analysis tools capable of nuanced interpretation.
  • IT Manager: On Monday morning, schedule a team meeting to brief the IT support staff on the research findings regarding gendered cyberbullying dynamics on platforms like TikTok, and instruct them to proactively monitor user reports for comments exhibiting 'emotional trauma responses' on posts related to sensitive topics, escalating any patterns or severe instances to the security team.
  • Business Strategist: On Monday morning, task a cross-functional team (including marketing, communications, and product development) to analyze how the company's online platforms and content strategies can better support 'emotionally processing and healing-oriented conversations,' particularly in times of national crisis, drawing inspiration from the supportive dynamics observed on female youth posts.
  • Researcher: On Monday morning, design a follow-up study proposal that specifically investigates the efficacy of different intervention strategies for 'emotional trauma responses' in cyberbullying, perhaps comparing the impact of direct moderation versus community-driven support mechanisms on platforms like TikTok, with a focus on gendered responses.
  • Policymaker: On Monday morning, draft a policy brief to relevant stakeholders outlining the research findings on gendered cyberbullying and the prevalence of 'emotional trauma responses' during national crises, recommending the development of targeted digital literacy programs for youth that address empathetic online communication and healthy coping mechanisms for dealing with sensitive content.
cyberbullying, school shootings, TikTok, gender differences, sentiment analysis, youth mental health
The Impact of Gamified Cyberbullying Trends on Adolescent Mental Health on TikTok in the U.S.
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
The Impact of Cyberbullying on Help-Seeking Among Depressed Young adults in the United States
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
Body Image Distress and Cyberbullying Among Adolescent Girls in the U.S.
AI Processed Human Approved

How common is body-related cyberbullying against adolescent girls on TikTok, and what forms does it take?

Gordon Amidu
Body Image Distress and Cyberbullying Among Adolescent Girls in the U.S.
2025
Key findings
  • Cyberbullying constituted 7.4% of total analyzed interactions, whereas non-cyberbullying comments comprised 92.6%.
  • Body shaming was the most prevalent cyberbullying behavior (41.68%), followed by insults (24.78%) and teasing (21.26%).
  • Neutral sentiment predominated user responses, followed by positive sentiment, with negative sentiment representing the smallest proportion.
  • Topic modeling revealed five primary themes: Appearance Monitoring, Body Commentary, Positive Affirmations, Social Comparison, and Identity Confusion.
What it means for you
  • CIO / IT Executive: Initiate a review of existing content moderation algorithms and reporting mechanisms to assess their effectiveness in detecting and flagging body shaming, insults, and teasing comments related to appearance on platforms frequented by adolescent girls, aiming to prioritize enhancements for these specific issue types.
  • IT Manager: Schedule a technical deep-dive meeting with the content moderation team to present the research findings on the prevalence of body shaming and insults on TikTok, and collaboratively identify specific keyword filters and pattern recognition strategies to implement within current moderation tools to better catch these behaviors.
  • Business Strategist: Develop a proposal for a new product feature or marketing campaign that leverages positive affirmations and counter-narratives to combat social comparison and identity confusion related to body image on social media platforms, referencing the research's thematic analysis of positive affirmations as a potential intervention.
  • Researcher: Begin drafting a follow-up research proposal that specifically investigates the effectiveness of different types of content moderation (e.g., AI-driven vs. human) in mitigating body shaming and insult-based cyberbullying on TikTok, and proposes a quantitative analysis of user sentiment shifts post-intervention.
  • Policymaker: Draft a preliminary policy brief for the relevant government agency, highlighting the study's quantitative data on the percentage of cyberbullying and the specific themes of harassment (body shaming, insults), and outlining the urgent need for platform-specific regulations and youth mental health intervention funding to address appearance-centered online harassment.
Body shaming, Cyberbullying, Adolescent girls, TikTok, Online harassment
Improving Self-Organization Capability in e-Learning using Soft System Methodology: A Case from Indonesia
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
A Research Agenda to Understand Drivers of Digital Gullibility
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
Digital Mental Health Resilience During Natural Disasters: A Scoping Review and Research Agenda
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
Service Learning in Information Systems Education: Pedagogical Approaches to Support Experiential Learning and Higher-level Thinking
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
Visualizing Platform Hubs of Smart City Mobility Business Ecosystems
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
IS Design Principles for Empowering Domain Experts in Innovation: Findings From Three Case Studies
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
How Do Technology Paradigms Influence Configurations of Contract Characteristics for Success of Inter-Organizational Outsourcing Projects, 1991–2009?
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
Managing Performance in Collaborative Networks: A Method for Defining Key Performance Indicators for Collaborative Business Models
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
Can Regulation Restore Authenticity? Evidence from Policies Against Online Review Suppression
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
The Process of Process Science – Generating Actionable Insights from Digital Trace Data
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
TOWARD CULTURAL–ETHICAL FIT IN AI GOVERNANCE: A GLOBAL TYPOLOGY OF GOVERNANCE PROFILES
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
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