Optimization of Intelligent Shopping Guide System of New Retail Fresh Supermarket Based on TAM Model: A Case Study in China Under COVID-19

Anthony Kong (Corresponding Author)

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

New retail fresh supermarket is an emerging supermarket service model in recent years, consumer behaviour is its focused problem. Affected by the COVID-19, panic buying of fresh food has become common, food waste and consumer dissatisfaction increased. In addition, many design deficiencies also influence consumer gratification with fresh supermarkets. Thus, this study explored the consumer psychology through questionnaires to ascertain the pain points of consumers, establish a model of ideal supermarket intelligent shopping guide systems based on the data analysis of 733 valid samples. The results show that (1) intelligent recommendation, product information and position search are essential to behavioural intention, (2) technical support affects consumer attitudes through the mediating effect of Compatibility and perceived ease of use, and ultimately affects users’ behavioral intentions, (3) perceived usefulness and perceived ease of use are mediate factors of the optimization of guide system with user’s attitude and behavioral intention.
Original languageEnglish
Title of host publicationProceedings of the 2023 2nd International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2023)
Subtitle of host publicationAtlantis Highlights in Intelligent Systems
PublisherAtlantis Press
Pages491-501
Number of pages11
ISBN (Electronic)2589-4919
ISBN (Print)978-94-6463-222-4
DOIs
Publication statusPublished - 28 Aug 2023

Keywords

  • New Retail
  • COVID-19
  • Raw Food Supermarket
  • Shopping Behavior
  • Intelligent Shopping Guidance System

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