A comprehensive framework for TIM students and faculty to conduct effective scoping reviews with AI assistance
This guide offers a clear, step-by-step method for using AI tools to conduct scoping reviews—from creating your review question to sharing your final insights. Along the way, we focus on keeping the process ethical, current, and easy to follow for both students and faculty.
Formulate clear and effective review questions
Conduct thorough and reproducible reviews
Use AI tools effectively throughout the process
Foster a collaborative learning community
Foundation of Scoping Reviews
Method to Produce Scoping Reviews
Updating Scoping Review Guide
Term | Definition |
---|---|
Boolean operators | Logical connectors (AND, OR, NOT) used in database searches to refine search results by including or excluding specific terms. |
Grey literature | Information produced outside of traditional publishing and distribution channels, such as reports, conference proceedings, and government documents. |
Human oversight | The involvement of human judgment and decision-making in monitoring, guiding, or intervening in automated systems to ensure ethical, accurate, and responsible outcomes. |
PRISMA-ScR | The Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews, a framework that provides guidelines for conducting and reporting scoping reviews. |
Scoping review | A type of literature review that maps key concepts, evidence, and research gaps in a field, typically without assessing the quality of the included studies. |
Systematic review | A structured and comprehensive review of existing research on a specific question, using a rigorous methodology to identify, appraise, and synthesize relevant studies. |
A scoping review gathers and examines a wide range of sources to show what is known and unknown. Gaps in the literature can inspire new business ideas or research questions. Within Technology Innovation Management (TIM), scoping reviews can inform venture pitches, new market analysis, business opportunities, new product development, process improvement, competitive landscape, technology disruptions, emerging business models, IP management, innovation ecosystems, research vignettes, TIM projects and theses, among other key areas.
In Technology Innovation Management, a scoping review helps you see what is already known—whether in blockchain commercialization, open innovation ecosystems, or emerging AI startups—and spot new opportunities. By combining human expertise with AI tools, TIM researchers can sift through large, varied studies, uncover practical insights from non-traditional sources, and guide innovation strategies for the future.
If your review question is narrowly defined, aims to evaluate the quality of interventions, or measures effectiveness (e.g., comparing success rates of two IP licensing strategies), a systematic review is more suitable.
In TIM, scoping reviews are especially valuable when:
Scoping reviews in TIM often follow one or more of five main frameworks:
Five-step outline that works well for fast-changing fields like fintech
Example: Map out literature on wearable technology for remote patient monitoring, capturing academic journals to patent filings and whitepapers.
Extends Arksey and O'Malley's model by stressing stakeholder engagement
Example: Engage accelerators and manufacturers in refining your review on IoT-based smart manufacturing.
Offers refined methodology for planning and conducting reviews
Example: Follow JBI's methodology to conduct a review on 3D-printing technologies for rapid prototyping.
Focuses on standardized reporting of scoping reviews
Example: Ensure your review on blockchain applications follows PRISMA-ScR guidelines for transparent reporting.
Incorporate AI-powered literature review tools for efficiency
Example: Leverage AI-based tools to accelerate your review on digital entrepreneurship ecosystems post-COVID-19.
AI can manage large volumes of diverse data—quickly and consistently—making it invaluable for scoping reviews in TIM. It helps teams move faster to market, discover better product-market fits, stay ahead of disruptive technologies, and uncover new opportunities or threats.
Overall impact: AI speeds up the research process and delivers more actionable insights, helping TIM teams move faster to market, discover better product-market fits, stay ahead of disruptive technologies, and uncover new opportunities or threats.
May capture low-quality studies with anecdotal claims about innovation incubation success without rigorous data.
High-level overview may provide insufficient depth for policy recommendations.
Diverse methodologies make it difficult to uniformly assess quality.
Risk of overemphasizing highly cited technology clusters and missing newer areas.
Combining diverse data can complicate thematic analysis.
AI might invent references or misattribute authors regarding cloud computing commercialization.
AI may oversimplify multi-stage innovation models, missing critical nuances about ecosystem stakeholders.
May reflect biases favoring Anglophone research or well-funded corporate labs.
AI might miss foundational works in technology transfer or early research.
AI-generated text might closely resemble existing literature without proper attribution.
In TIM scoping reviews, human oversight involves researchers, faculty, or industry experts monitoring AI outputs for domain accuracy, evaluating the suitability of included studies, and intervening when AI misinterprets key concepts. TIM practitioners must blend AI's efficiency with their contextual knowledge of emerging technology markets, investor behaviors, and regulatory landscapes.
Organizing a scoping review in TIM often involves hundreds of sources—from academic articles to market research or new market analyses.
Create folders for IP studies, digital platforms research, policy documents, etc. to keep your references structured and easily accessible.
Generate references in APA, Harvard, or custom in-house styles with a single click, saving time and ensuring consistency.
Allow research teams across universities or technology labs to co-manage references in real time for seamless teamwork.
Tool | Key Features | Best For |
---|---|---|
Zotero
|
|
Quickly saving references from webpages or technology news |
Mendeley
|
|
Discovering new papers in IoT, AI, or digital entrepreneurship |
EndNote
|
|
Extensive R&D portfolio analyses and complex projects |
Conducting a scoping review requires a structured approach. This ensures clarity, transparency, and reliability throughout the research process. Part 2 outlines a step-by-step method tailored for TIM students, faculty and professionals who are integrating AI tools to enhance efficiency and precision in the scoping review process.
"AI enhances efficiency in literature reviews but does not replace human expertise. Use AI for automating repetitive tasks, such as summarization and categorization, while relying on human judgment for critical analysis, theoretical alignment, and decision-making."
Each step integrates AI tools to enhance efficiency while maintaining human oversight. The following sections detail each step in the process, providing practical guidance on implementing AI-assisted techniques while ensuring rigorous, ethical research practices.
A scoping review requires a broad and exploratory review question that captures the full range of relevant studies and perspectives.
The PCC framework ensures clarity in scoping review formulation, helping TIM students and faculty define their focus areas effectively.
Mid-sized manufacturing firms
Adoption of Industry 4.0 technologies (IoT, AI, blockchain)
North American smart manufacturing landscape
What are the primary barriers and facilitators influencing the adoption of Industry 4.0 technologies in mid-sized Canadian manufacturing firms?
Clearly defined research question
Structured using PCC or another appropriate framework
Review objectives
Statement outlining what the review aims to achieve
Keywords and search terms
Initial set of keywords, Boolean operators, and alternative terms
Scope of the review
Defined boundaries including inclusion/exclusion criteria
A thorough and systematic search for articles is essential to ensure that the scoping review captures all relevant literature. The search process should be iterative, transparent, and broad enough to identify diverse sources of information.
Tool | Key Features | Best For |
---|---|---|
ChatGPT
|
|
Query formulation and refinement |
Consensus
|
|
Finding reliable, high-consensus studies |
Perplexity
|
|
Finding connections between different studies |
("artificial intelligence" OR "machine learning" OR "AI-driven analytics") AND ("venture capital" OR "startup investment") AND ("decision-making" OR "risk assessment" OR "funding strategies")
To ensure a rigorous and high-quality scoping review, authors and reviewers should systematically assess their work against the following checklist. This checklist aligns with the key steps and considerations outlined in this guide for Technology Innovation Management (TIM) research.
This section outlines the process for keeping the Scoping Review Guide current and relevant. As technology evolves, particularly AI tools, this guide must adapt to reflect emerging best practices, methodologies, and ethical considerations.
Quarterly Reviews
Assessment of current content and identification of areas for improvement
Semi-Annual Updates
Implementation of revisions based on feedback and technological developments
Critical Updates
Immediate implementation for significant AI tool changes or methodological advancements
Semantic Versioning
Using MAJOR.MINOR.PATCH format (e.g., v1.2.3) to track changes
Changelog Documentation
Detailed records of all modifications with justifications
Archive Access
Previous versions remain accessible for reference and continuity
Version | Date | Key Changes | Contributors |
---|---|---|---|
v1.0.0 | March 2025 | Initial release | TIM Faculty |
This guide is a living document that improves through community contributions. There are multiple ways for TIM students, faculty, and practitioners to help enhance this resource.
"This guide was developed with a combination of human expertise and AI assistance. AI tools were used to draft initial content, organize information, and suggest relevant examples. All AI-generated content was reviewed, refined, and approved by TIM faculty with expertise in literature reviews, research methods, and technology innovation management."
Time Savings with AI
Average Sources Analyzed
Increased Insight Discovery
AI+Human Accuracy Rate
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