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Boundary Spanning and Practical Impact in IS Research: A Bourdieusian Analysis
AI Processed Human Approved

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

Stephen McCarthy, Hendrik Scholta, Geir Inge Hausvik, Peter André Busch
Boundary Spanning and Practical Impact in IS Research: A Bourdieusian Analysis
Information Systems Journal (ISJ) · 2025
Key findings
  • IS practitioner doctorates facilitate knowledge exchange through boundary-spanning activities including research design adaptation, multi-channel dissemination, and creating symbolic discourse.
  • Practical impact progresses through proof-of-concept, proof-of-value, and proof-of-use stages, each requiring different combinations of social, cultural, economic, and symbolic capital.
  • Environmental forces such as academic vs. practice doxa (institutional norms) and habitus (professional dispositions) create positional conflicts that require active negotiation and tailored incentives to sustain engagement.
What it means for you
  • CIO / IT Executive: On Monday morning, schedule a 30-minute meeting with your direct reports to initiate a 'practice impact review' focused on one ongoing IS project. Ask each person to identify one specific academic insight or research finding from a recent external study or internal research initiative that could be directly applied to improve that project's current proof-of-concept or proof-of-value stage, and assign them to explore this application by end of week.
  • IT Manager: On Monday morning, identify one specific, recent academic paper or conference proceeding relevant to a current team challenge. Forward this paper to your team with a concise note asking for a brief, 1-2 sentence summary of its most practical takeaway and how it *might* apply to your current proof-of-value stage objective by Tuesday afternoon.
  • Business Strategist: On Monday morning, review the key performance indicators (KPIs) of one strategic business initiative currently underway. Identify which KPIs are not meeting expectations and, using the 'proof-of-value' framework, draft a one-page hypothesis on how a novel IS application or process, potentially informed by academic research, could demonstrably improve these specific KPIs within the next quarter.
  • Researcher: On Monday morning, select one recent academic publication where you are the lead author and identify its 'proof-of-use' stage potential. Draft a single-slide executive summary that articulates the core problem addressed, the practical solution proposed, and one tangible benefit for a specific industry practitioner role (e.g., IT manager, business analyst), and share it with three relevant practitioner contacts for feedback by Wednesday.
  • Policymaker: On Monday morning, review the current grant application criteria for technology innovation funding. Identify if and how 'demonstrable practical impact' is explicitly assessed, and draft a brief proposal to incorporate a specific requirement for applicants to detail their strategy for achieving 'proof-of-value' or 'proof-of-use' within a defined timeframe, alongside theoretical contributions.
academia-practice gap, boundary spanning, design science research, engaged IS scholarship, practical impact, theory of practice
Affordance-Based Pathway Model of Social Inclusion: A Case Study of Virtual Worlds and People With Lifelong Disability
AI Processed Human Approved

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

Karen Stendal, Maung K. Sein, Devinder Thapa
Affordance-Based Pathway Model of Social Inclusion: A Case Study of Virtual Worlds and People With Lifelong Disability
Journal of the Association for Information Systems · 2026
Key findings
  • Identified three functional affordances (communicability, mobility, and personalizability) and two social affordances (engageability and self-actualizability) crucial for social inclusion.
  • Established that the actualization of functional affordances enables and dynamically interacts with social affordances to foster interpersonal relationships and community participation.
  • Discovered that outcomes achieved by actualizing specific affordances serve as facilitating conditions that support the perception and realization of additional affordances.
  • Extended affordance theory by demonstrating a feedback loop where social engagement refines and enhances the perception and use of basic functional capabilities.
What it means for you
  • CIO / IT Executive: On Monday morning, task your accessibility team to conduct an initial assessment of our current platform's 'communicability' features (e.g., real-time chat, group messaging, avatar-based interaction quality) against the research's identified functional affordances to understand potential barriers and opportunities for individuals with disabilities.
  • IT Manager: On Monday morning, schedule a 30-minute working session with your frontline support staff to review existing user feedback logs for mentions of difficulty with navigation, communication, or customization within our virtual environment, specifically looking for patterns that might align with limitations in perceived 'mobility' or 'personalizability' affordances.
  • Business Strategist: On Monday morning, initiate a competitive analysis focusing on how emerging virtual platforms or digital communities are leveraging 'engageability' and 'self-actualizability' affordances to foster user connection and content creation, particularly noting any strategies that might appeal to or benefit users with disabilities.
  • Researcher: On Monday morning, begin drafting a protocol for a pilot study within our organization's virtual world that focuses on measuring the impact of enhanced 'communicability' features on user-reported feelings of 'engageability' and 'self-actualizability' among a diverse user group, potentially including participants with disabilities.
  • Policymaker: On Monday morning, convene a brief meeting with your advisory committee to discuss how current digital inclusion policies might be strengthened by explicitly incorporating the research's identified 'functional affordances' (communicability, mobility, personalizability) and 'social affordances' (engageability, self-actualizability) as measurable criteria for assessing technological accessibility and support for social participation.
Social Inclusion, Virtual Worlds, People With Lifelong Disability, Affordances, Second Life, ICT
Social mobile analytics and cloud computing: a big data analytical approach
AI Processed Human Approved

What are the main benefits, challenges, and technical solutions when combining social, mobile, analytics, and cloud technologies?

Farhad Ali, Habib Ullah Khan, Shah Nazir
Social mobile analytics and cloud computing: a big data analytical approach
2026
Key findings
  • Identified main collaborative entities within SMAC ecosystems, including smartphones, cloud platforms, crowd participants, and environmental sensors.
  • Summarized key organizational and societal benefits such as enhanced decision-making, operational cost reduction, improved productivity, and expanded social engagement.
  • Classified primary adoption challenges, focusing on data privacy, security vulnerabilities, scalability limits, energy consumption, and system interoperability.
  • Compiled existing technical solutions from literature, highlighting techniques such as attribute-based encryption, anonymization methods, and hyper-heuristic frameworks.
What it means for you
  • CIO / IT Executive: On Monday morning, initiate a cross-departmental working group focused on assessing our current SMAC infrastructure against the identified adoption challenges (privacy, security, scalability, energy, interoperability) using the research's findings as a framework, and schedule an initial meeting for next week.
  • IT Manager: On Monday morning, begin a review of our existing data anonymization protocols and encryption techniques, cross-referencing them with the 'existing technical solutions' highlighted in the research to identify immediate gaps or opportunities for enhancement within our current cloud and mobile analytics platforms.
  • Business Strategist: On Monday morning, schedule a 30-minute brainstorming session with your core team to identify one specific business process that could significantly benefit from SMAC integration, and during that session, identify the most critical adoption challenge from the research that needs to be addressed first for this specific process.
  • Researcher: On Monday morning, create a detailed spreadsheet to categorize the 75 papers reviewed in this study by the specific SMAC component (Social, Mobile, Analytics, Cloud), the primary adoption challenge addressed, and the technical solution proposed, to facilitate further meta-analysis.
  • Policymaker: On Monday morning, draft a request for a preliminary impact assessment on user privacy and cybersecurity risks associated with the widespread adoption of SMAC technologies within our jurisdiction, drawing upon the challenges identified in the research as key areas to investigate.
SMAC Framework, Big Data, Cloud Computing, Social Media Analytics, Mobile Computing, Data Security
An Empirical Investigation of Cloud Computing and Environmental Performance of Nations: Implications for Shared Responsibility in Cloud Computing
AI Processed Human Approved

How does cloud computing affect energy use and carbon emissions across host and user countries?

Jooho Kim, Jiyong Park, Jason Dedrick
An Empirical Investigation of Cloud Computing and Environmental Performance of Nations: Implications for Shared Responsibility in Cloud Computing
Journal of the Association for Information Systems · 2025
Key findings
  • Access to cloud services generally enhances environmental efficiency by reducing national energy and carbon intensities associated with IT services.
  • Countries hosting cloud data centers experience higher local energy and carbon intensities due to heavy physical infrastructure demands.
  • Neighboring countries benefit from green cloud IT services without incurring adverse environmental costs on their local IT capital.
  • A shared responsibility model based on multilayered technology architecture is proposed to divide environmental accountability between cloud providers and users.
What it means for you
  • CIO / IT Executive: On Monday morning, initiate a review of our current cloud infrastructure's geographical distribution and identify which of our cloud services are hosted in countries that are net importers of cloud services (i.e., benefiting from efficiency gains) versus countries that are net hosts of data centers. Then, begin drafting an internal memo to your team outlining the need to assess the environmental footprint of our chosen cloud providers, specifically focusing on the geographical location of their data centers.
  • IT Manager: On Monday morning, compile a list of all cloud services currently utilized by your department and identify the primary cloud provider(s) for each. Then, locate and review the public documentation of these providers regarding their data center locations and any publicly available environmental sustainability reports or initiatives.
  • Business Strategist: On Monday morning, begin by identifying which key business processes or customer-facing services are heavily reliant on cloud computing. Then, investigate if these services are currently being delivered from cloud infrastructure located in countries that are significant importers of cloud services or from countries that are major hosts of data centers, and flag this for further cost-benefit analysis that includes potential environmental externalities.
  • Researcher: On Monday morning, start by drafting an email to your colleagues or supervisor proposing a follow-up study that quantifies the specific cross-border environmental impacts for a subset of countries using the methodologies outlined in this paper. Include a brief outline of the data you would need to gather, such as national IT service import/export data and detailed data center location information for key cloud providers.
  • Policymaker: On Monday morning, draft a preliminary policy brief for your relevant committee or ministry that summarizes the key findings of this research regarding the uneven distribution of environmental burdens from cloud computing. Specifically, highlight the need for international dialogue on shared responsibility and propose an initial step to investigate incorporating environmental footprint data into public procurement policies for cloud services.
Cloud Computing, IT Capital, IT Services, Digital Responsibility, Shared Responsibility, Sustainability
STRUCTURING READINESS FOR AI INNOVATION: THE ROLE OF THE DESIGN CHALLENGE BRIEF AS A COORDINATION AND GATEKEEPING ARTEFACT
AI Processed Human Approved

How can teams evaluate whether an artificial intelligence project is ready to launch?

Jennifer Hehn, Franziska Anna Röckel, Benjamin van Giffen
STRUCTURING READINESS FOR AI INNOVATION: THE ROLE OF THE DESIGN CHALLENGE BRIEF AS A COORDINATION AND GATEKEEPING ARTEFACT
ECIS 2026 · 2026
Key findings
  • The study outlines a preliminary three-phase qualitative model for establishing AI project readiness: divergent exploration, negotiation/translation, and convergent alignment, though these findings are descriptive and lack statistical testing.
  • The Design Challenge Brief is shown to act as a gatekeeping artifact that structures readiness reviews and allows teams to selectively revisit earlier project assumptions without resetting the entire process.
  • The study is limited by its small qualitative sample of five projects and its setting within a structured, university-led innovation lab, which may restrict generalizability to less-structured corporate settings.
What it means for you
  • CIO / IT Executive: Draft and mandate a standard 'Design Challenge Brief' template that all AI project champions must complete and get approved before receiving formal project launch funding.
  • IT Manager: Gather your AI project team for a 1-hour workshop to map your current pre-project planning stage to the three phases of divergent exploration, negotiation/translation, and convergent alignment, explicitly documenting how you will handle fluid data availability.
  • Business Strategist: Audit your pipeline of proposed AI initiatives and flag any project that has not yet completed a collaborative 'Design Challenge Brief' to prevent launching projects with high uncertainty around non-deterministic outcomes.
  • Researcher: Draft a research proposal and survey instrument to test the generalizability of the three-phase AI readiness model across a quantitative sample of 100+ corporate AI projects outside of academic lab settings.
  • Policymaker: Integrate a 'Design Challenge Brief' gatekeeping requirement into your public sector AI procurement and funding frameworks to ensure public agencies evaluate data readiness and outcome uncertainties before awarding AI contracts.
AI innovation, readiness work, design challenge brief, boundary objects, gatekeeping
DESIGNING FOR IMPERFECT PROMPTS: A SIMULATION-BASED EVALUATION OF AN LLM-BASED ENTERPRISE DATA ASSISTANT USING KNOWLEDGE GRAPHS
AI Processed Human Approved

Which approach best helps AI assistants translate imperfect user prompts into accurate database queries?

Niklas Wagner, Alexander Mdche
DESIGNING FOR IMPERFECT PROMPTS: A SIMULATION-BASED EVALUATION OF AN LLM-BASED ENTERPRISE DATA ASSISTANT USING KNOWLEDGE GRAPHS
ECIS 2026 · 2026
Key findings
  • The KG-based mediation statistically outperformed the schema-based mediation across Precision, Recall, and F1-Score metrics.\n- For GPT-4.1, the KG-based approach achieved a Precision of 90.67% (compared to 69.05% for schema-based) and an F1-Score of 89.47% (compared to 71.02% for schema-based).\n- For Claude Sonnet 4, the KG-based approach achieved a Precision of 87.23% (compared to 75.17% for schema-based) and an F1-Score of 90.29% (compared to 82.17% for schema-based), while Recall remained statistically comparable (93.52% vs 92.56%).\n- The study is limited by its focus on a single-enterprise setting within a CFO unit, a finite dataset of 158 interactions from 29 users, and reliance on a simulation-based evaluation instead of live field deployments.
What it means for you
  • CIO / IT Executive: Issue a directive to transition the enterprise's LLM-based data assistant architecture away from simple schema-based semantic similarity matching and onto a Knowledge Graph-based mediation layer constructed from database schemas to capture the demonstrated 12% to 21% precision improvements.
  • IT Manager: Instruct your database and engineering teams to begin constructing a Knowledge Graph from your current database schemas to serve as a semantic mediation layer for your LLM assistant, replacing manual prompt engineering.
  • Business Strategist: Launch a pilot program within the CFO business unit to deploy the Knowledge Graph-based data assistant, leveraging its verified ability to resolve incomplete, domain-specific prompts into accurate database queries for business users.
  • Researcher: Draft a research proposal to test the Knowledge Graph-based mediation layer in a live, real-world field deployment to gather empirical performance data beyond the current study's simulation of 158 interactions across 29 users.
  • Policymaker: Draft an internal data governance policy requiring that all natural-language LLM interfaces querying corporate databases must use a schema-derived Knowledge Graph mediation layer to ensure structural query alignment and prevent inaccurate data retrieval.
Large Language Models, Enterprise Data Assistants, Text-to-SQL, Knowledge Graphs, Design Science Research
ORCHESTRATION PARADOXES IN NATIONAL QUANTUM COMPUTING INNOVATION ECOSYSTEMS
AI Processed Human Approved

What competing tensions and trade-offs do leaders face when guiding national quantum computing ecosystems?

Jori Taipale, Olli Tyrväinen, Tuure Tuunanen, Joel Mero, Teiko Heinosaari
ORCHESTRATION PARADOXES IN NATIONAL QUANTUM COMPUTING INNOVATION ECOSYSTEMS
ECIS 2026 · 2026
Key findings
  • Organizing tensions were identified as the most frequent paradox, specifically focusing on the trade-offs between collaboration vs. resource competition and guidance vs. flexibility.
  • Performance tensions emerged regarding resource allocation between software vs. hardware development and building a shared vision vs. individual firm survival.
  • Belonging tensions highlighted a 'godfather' paradox, where the ecosystem must balance the state's role as a major supportive funder and customer with the ultimate goal of corporate independence.
  • Learning tensions were characterized by the challenge of managing multi-talent knowledge development versus narrow technology specialization.
  • The study is limited by its single qualitative case context in Finland with a small sample of 15 informants, requiring caution when applying these findings to other national contexts.
What it means for you
  • CIO / IT Executive: Schedule a 9:00 AM meeting with your lead enterprise architect to audit your current quantum-readiness roadmap, establishing a formal policy that divides software development and hardware access investments 50/50 to hedge against the performance tension of committing prematurely to a single unproven hardware stack.
  • IT Manager: Create a bi-weekly 1-hour 'Quantum Cross-Training' slot in your team's calendar starting this Friday, pairing your specialized quantum physics PhDs with your generalist cloud engineers to address the learning tension between narrow technical specialization and broad-based systems integration.
  • Business Strategist: Perform a revenue dependency audit to calculate the percentage of your quantum business unit's funding derived from state grants versus commercial clients, and draft a pitch deck for two private-sector pilots to actively transition away from 'godfather' state-funding reliance.
  • Researcher: Draft a pre-competitive collaboration agreement template to send to a peer researcher at a competing institution, outlining a shared framework for baseline algorithm testing while clearly defining IP boundaries to manage the tension of collaboration versus resource competition.
  • Policymaker: Draft a revision for the upcoming national quantum funding round guidelines that introduces a 'co-investment requirement,' mandating that state-funded consortia secure at least 25% of their budget from private corporate buyers to counter the 'godfather' dependency paradox.
Ecosystem orchestration, Paradox theory, Quantum computing innovation ecosystem, Explorative case study, Interpretive qualitative research
TOWARDS DESIGN PRINCIPLES FOR TEACHING INDUSTRY 4.0 COMPETENCIES TO CS/IS STUDENTS
AI Processed

How can educators effectively teach modern industrial software skills without expensive physical equipment?

Felix Salcher
TOWARDS DESIGN PRINCIPLES FOR TEACHING INDUSTRY 4.0 COMPETENCIES TO CS/IS STUDENTS
ECIS 2026 · 2026
Key findings
  • Eight design principles were established, emphasizing virtualization, containerization, and problem-based learning cases as alternatives to expensive learning factories.\n- Preliminary course evaluation yielded positive descriptive feedback, with a mean rating of 4.43 out of 5 across satisfaction categories.\n- No formal statistical significance tests were performed due to the pilot nature of the study and the small, specific evaluation sample.\n- The pilot is limited by a very small sample size (9 respondents from a single cohort) and relies on subjective student perceptions rather than objective competency-based assessments.\n- Students noted difficulty adapting to the course's fast pace and programming requirements, highlighting a need for aligned prerequisites.
What it means for you
  • CIO / IT Executive: Direct your enterprise architecture team to draft a transition plan to replace physical IT hardware training labs with virtualized, containerized sandbox environments (e.g., Docker/Kubernetes) to reduce infrastructure costs and align onboarding with modern Industry 4.0 software architectures.
  • IT Manager: Review the programming prerequisites of your junior developers and assign them a structured, hands-on troubleshooting task using a containerized microservice mock-up on Monday morning to assess their readiness for complex Industry 4.0 integration projects.
  • Business Strategist: Reallocate a portion of next quarter's talent development budget away from high-cost physical equipment training and toward scalable, software-based virtual simulators to cost-effectively build digital twin and data architecture competencies.
  • Researcher: Draft a research proposal to conduct a multi-institution comparative study on these eight design principles, incorporating objective pre- and post-intervention technical testing rather than relying on subjective student feedback to measure competency gains.
  • Policymaker: Create a state-level educational grant initiative that incentivizes higher education institutions to update computer science curricula with virtualization-based Industry 4.0 frameworks, shifting funding priority away from physical learning factories.
Design Principles, Design Science Research, Industry 4.0, Smart Manufacturing
THE ANATOMY OF A DESIGN CHALLENGE FOR INITIATING AI INNOVATION
AI Processed Human Approved

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

Franziska Anna Röckel, Benjamin van Giffen, Andreas Janson, Jennifer Hehn
THE ANATOMY OF A DESIGN CHALLENGE FOR INITIATING AI INNOVATION
ECIS 2026 · 2026
Key findings
  • The study empirically validated a structural anatomy for the Design Challenge consisting of four robust elements (verb, object of innovation, target group, context) and three plastic elements (internal data, technology, potential), which was supported across all 42 cases analyzed.
  • The robust elements were validated to successfully create a stable, shared identity and common direction among diverse team members, acting as a center of authority.
  • The plastic elements were shown to successfully absorb technological uncertainty, providing a flexible framework for teams to negotiate and adapt to AI's emergent capabilities over time.
  • The qualitative analysis identified three distinct nuances in shaping the 'object of innovation' (modular, abstract, and space) that guide teams toward either incremental or more radical innovation pathways.
What it means for you
  • CIO / IT Executive: Mandate that all upcoming AI project proposals use a standardized 'Design Challenge' charter template structured around the 4 robust elements (verb, object of innovation, target group, context) and 3 plastic elements (internal data, technology, potential), explicitly forbidding teams from locking in a rigid technical architecture in their initial pitch.
  • IT Manager: Gather your interdisciplinary project team for a 60-minute workshop on Monday morning to co-create a 'Design Challenge' statement, explicitly defining the stable 'robust' elements to align the business and tech members, while leaving the 'plastic' elements (like specific data sources and AI models) open as flexible targets to be negotiated as the project progresses.
  • Business Strategist: Review your company's AI project portfolio on Monday morning and intentionally rewrite the 'object of innovation' for each project: frame them as 'modular' if you need predictable, incremental improvements, or rewrite them as 'space-based' (e.g., focused on broad capabilities) if you want to push the team toward radical, disruptive business model innovation.
  • Researcher: Update your qualitative coding scheme for ongoing field studies of AI adoption to track how frequently and at what project stages teams modify the 'plastic' elements (internal data, technology, potential) versus the 'robust' elements of their project charters to measure the empirical threshold where technological uncertainty triggers project misalignment.
  • Policymaker: Revise the application guidelines for the upcoming public AI innovation grant cycle to replace rigid 'technical specifications' requirements with a mandatory 'Design Challenge' framework, scoring applicants on the clarity of their robust elements (target group, context) and the adaptive flexibility of their plastic elements (data and technology integration plans).
Design Challenge, AI Innovation, Boundary Object, Anatomy, Interdisciplinary Collaboration, Problem Formulation
Capturing the “Social” in Social Networks: The Conceptualization and Empirical Application of Relational Quality
AI Processed

How do activity levels and connection counts shape the quality of employee interactions on corporate social networks?

Christian Meske, Iris Junglas, Matthias Trier, Johannes Schneider, Roope Jaakonmäki, Jan vom Brocke
Capturing the “Social” in Social Networks: The Conceptualization and Empirical Application of Relational Quality
Journal of the Association for Information Systems · 2025
Key findings
  • Relational quality is a distinct and relevant dimension that complements traditional structural social network analysis (SNA), which typically only focuses on network structure.
  • The study identifies and measures four key facets of relational quality: being personal, being curious, being polite, and sharing.
  • Different types of users exhibit distinct patterns of relational quality; for instance, 'connectors' (users with many connections but low activity) are the most personal, while 'broadcasters' (users with high activity but few connections) share the most resources.
  • As a user's activity (e.g., number of posts) increases, their interactions tend to become less personal, curious, and polite, while their sharing of resources increases.
  • In contrast, as a user's number of connections grows, their interactions become more personal and curious, but they tend to share fewer resources.
Enterprise Social Network, Social Capital, Relational Quality, Social Network Analysis, Linguistic Analysis, Computational Research
Designing and Implementing Digital Twins in the Energy Grid Sector
AI Processed Human Approved

How can energy grid companies successfully design and implement digital twins?

Christian Meske, Karen S. Osmundsen, Iris Junglas
Designing and Implementing Digital Twins in the Energy Grid Sector
MIS Quarterly Executive · 2021
Key findings
  • The digital twin provides real-time and historical insights into the grid's status, enabling proactive maintenance, prediction of component failures, and more efficient management of power loads.
  • It serves as a powerful simulation tool to model future scenarios, such as the impact of increased electrification from electric ferries, allowing for better long-term planning and investment.
  • Successful implementation requires a strong focus on organizational learning, innovative co-creation with technology partners, and continuous feedback from end-users throughout the project.
  • The project highlighted the critical importance of evolving data governance, forcing the company to tackle complex issues of data security, integration, and standardization to unlock the full potential of the digital twin.
Digital Twin, Energy Sector, Grid Management, Digital Transformation, Organizational Learning, Co-creation, Data Governance
REGULATING EMERGING TECHNOLOGIES: PROSPECTIVE SENSEMAKING THROUGH ABSTRACTION AND ELABORATION
AI Processed

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

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