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Food Traceability System Design Incorporating AI Chatbots: Promoting Consumer Engagement with Prepared Foods.

Bingjie Lu1, Decheng Wen1, Han Li2

  • 1School of Management, Shandong University, Jinan 250100, China.

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Summary

An artificial intelligence (AI) traceability assistant enhances consumer engagement with food traceability systems. This AI tool improves perceived ease of use, especially when consumers perceive higher product risks.

Keywords:
artificial intelligenceconsumer engagementconsumer responsesfood packagingfood qualityfood traceability systemperception of system ease of useprepared foodstraceability system design

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Area of Science:

  • Food Science
  • Consumer Behavior
  • Information Systems

Background:

  • Industrialized food processing increases supply chain complexity and consumer concerns about food safety.
  • Traditional traceability systems may cause information overload, hindering effective risk communication.
  • Consumer interest in food traceability is rising due to increased awareness of food-related risks.

Purpose of the Study:

  • To design and evaluate an AI traceability assistant to optimize traditional food traceability systems.
  • To investigate the impact of AI traceability assistant design on consumer engagement behaviors.
  • To explore the mediating role of perceived system ease of use and the moderating role of perceived product risk.

Main Methods:

  • The study utilized information overload theory and designed an AI traceability assistant.
  • Three online scenario experiments were conducted using prepared foods (Kung Pao chicken, fish-flavored shredded pork, pickled fish) and traceability tasks (preservatives, sweeteners, drug residues).
  • A total of 747 valid responses were collected to analyze the AI assistant's effects.

Main Results:

  • The AI traceability assistant significantly promoted positive consumer engagement behaviors.
  • Perceived system ease of use mediated the positive effect of the AI assistant on engagement.
  • Perceived product risk positively moderated the relationship between the AI assistant and perceived ease of use, strengthening the mediation.

Conclusions:

  • AI traceability assistants can effectively enhance consumer engagement in food traceability.
  • System design should consider perceived ease of use and product risk to maximize AI assistant effectiveness.
  • Findings offer theoretical insights and practical guidance for implementing digital traceability solutions in the food industry.