Generative AI, cognitive load, and supply chain risk perception: the moderating role of AI literacy

No abstract is available for this paper.

• Publication year

  2025

• Venue

  International Journal of Logistics Research and Applications

• Publication date

  2025-11-05

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1080/13675567.2025.2584305
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Generative artificial intelligence (GenAI) revolution: A deep dive into GenAI adoption

  2025cited by this paper
• Collaborative AI in the workplace: Enhancing organizational performance through resource-based and task-technology fit perspectives

  2025cited by this paper
• The Usage of AI in Teaching and Students’ Creativity: The Mediating Role of Learning Engagement and the Moderating Role of AI Literacy

  2025cited by this paper
• Not easy to "like": How does cognitive load influence user engagement in online reviews?

  2025cited by this paper
• The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers

  2025cited by this paper
• Generative AI: Boosting Adaptability and Reducing Workplace Overload

  2024cited by this paper
• Generative AI usage and sustainable supply chain performance: A practice-based view

  2024cited by this paper
• Generative AI-enabled supply chain management: A coordination theory perspective

  2024cited by this paper
• Artificial intelligence in supply chain management: A systematic literature review of empirical studies and research directions

  2024cited by this paper
• Using Augmentation-Based AI Tool at Work: A Daily Investigation of Learning-Based Benefit and Challenge

  2024cited by this paper
• Examining generative AI user addiction from a C-A-C perspective

  2024cited by this paper
• Uncovering the Research Hotspots in Supply Chain Risk Management from 2004 to 2023: A Bibliometric Analysis

  2024cited by this paper
• Clarifying supply chain disruption and operational resilience relationship from a threat-rigidity perspective: Evidence from small and medium-sized enterprises

  2024cited by this paper
• AI literacy and its implications for prompt engineering strategies

  2024cited by this paper
• AI literacy for users – A comprehensive review and future research directions of learning methods, components, and effects

  2024cited by this paper
• Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education

  2024cited by this paper
• Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review

  2024cited by this paper
• The effects of generative AI’s human-like competencies on clinical decision-making

  2024cited by this paper
• Generative AI

  2023cited by this paper
• Evaluating Model Fit of Measurement Models in Confirmatory Factor Analysis

  2023cited by this paper
• Generative AI at Work

  2023cited by this paper
• Design and validation of the AI literacy questionnaire: The affective, behavioural, cognitive and ethical approach

  2023cited by this paper
• From natural language to simulations: applying AI to automate simulation modelling of logistics systems

  2023cited by this paper
• AI-based forecasting for optimised solar energy management and smart grid efficiency

  2023cited by this paper
• Development of the “scale for the assessment of non-experts’ AI literacy” – An exploratory factor analysis

  2023cited by this paper
• Algorithmic extremism? The securitization of artificial intelligence (AI) and its impact on radicalism, polarization and political violence

  2023cited by this paper
• The GenAI is out of the bottle: generative artificial intelligence from a business model innovation perspective

  2023cited by this paper
• Supply chain resilience to climate change inflicted extreme events in agri-food industry: The role of social capital and network complexity

  2023cited by this paper
• Artificial intelligence for supply chain management: Disruptive innovation or innovative disruption?

  2023cited by this paper
• Generative artificial intelligence and its applications in materials science: Current situation and future perspectives

  2023cited by this paper
• Green hydrogen supply chain risk analysis: A european hard-to-abate sectors perspective

  2023cited by this paper
• Challenge or hindrance? How and when organizational artificial intelligence adoption influences employee job crafting

  2023cited by this paper
• NON‐RESPONSE BIAS IN SURVEY‐BASED ENTREPRENEURSHIP RESEARCH: A REVIEW, INVESTIGATION, AND RECOMMENDATIONS

  2022cited by this paper
• Artificial intelligence-driven risk management for enhancing supply chain agility: A deep-learning-based dual-stage PLS-SEM-ANN analysis

  2022cited by this paper
• Solving the shortest path interdiction problem via reinforcement learning

  2021cited by this paper
• The preliminary supply chain lessons of the COVID-19 disruption—What is the role of digital technologies?

  2021cited by this paper
• Understanding Cognitive Load in Digital and Online Learning: a New Perspective on Extraneous Cognitive Load

  2021cited by this paper
• Conceptualizing AI literacy: An exploratory review

  2021cited by this paper
• Social desirability bias in PSM surveys and behavioral experiments: Considerations for design development and data collection

  2021cited by this paper
• Supply chain risk management and operational performance: The enabling role of supply chain integration

  2020cited by this paper
• Controlling social desirability bias: An experimental investigation of the extended crosswise model

  2020cited by this paper
• What is AI Literacy? Competencies and Design Considerations

  2020cited by this paper
• Organizational Behavior and Human Decision Processes

  2019cited by this paper
• Developing a Broadly Applicable Measure of Risk Perception

  2018cited by this paper
• Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

  2018cited by this paper
• Understanding Is Key: An Analysis of Factors Pertaining to Trust in a Real-World Automation System

  2018cited by this paper
• The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics

  2018cited by this paper
• Supply chain risk management and artificial intelligence: state of the art and future research directions

  2018cited by this paper
• Ethical Considerations in Artificial Intelligence Courses

  2017cited by this paper
• Deep Learning

  2016cited by this paper
• An Easy Approach to Exploratory Factor Analysis: Marketing Perspective

  2016cited by this paper
• Cognitive Offloading.

  2016cited by this paper
• The Effect of Cognitive Load on Economic Decision Making

  2015cited by this paper
• Supply chain risk management: a literature review

  2015cited by this paper
• A concept map-embedded educational computer game for improving students' learning performance in natural science courses

  2013cited by this paper
• Development of an instrument for measuring different types of cognitive load

  2013cited by this paper
• Technostress: Technological Antecedents and Implications

  2011cited by this paper
• Complacency and Bias in Human Use of Automation: An Attentional Integration

  2010cited by this paper
• Buyer perceptions of supply disruption risk: A behavioral view and empirical assessment

  2010cited by this paper
• Integrating cognitive load theory and concepts of human-computer interaction

  2010cited by this paper
• The Consequences of Technostress for End Users in Organizations: Conceptual Development and Empirical Validation

  2008cited by this paper
• The mediation of external variables in the technology acceptance model

  2006cited by this paper
• Risk Management in Sustainable Supply Chain Management (SSCM): Lessons Learnt from the Case of GMO-Free Soybeans

  2006cited by this paper
• The Sources of Four Commonly Reported Cutoff Criteria

  2006cited by this paper
• Common method biases in behavioral research: a critical review of the literature and recommended remedies.

  2003cited by this paper
• Guidelines for the process of cross-cultural adaptation of self-report measures.

  2000cited by this paper
• Task-Technology Fit and Individual Performance

  1995cited by this paper
• Cognitive Load During Problem Solving: Effects on Learning

  1988cited by this paper
• Perception of risk.

  1987cited by this paper
• Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

  1981cited by this paper
• Threat-rigidity effects in organizational behavior: A multilevel analysis.

  1981cited by this paper

• No citing papers are available for this paper.