Analyzing AI-Generated Packaging's Impact on Consumer Satisfaction With Three Types of Datasets

IF 0.5 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

International Journal of Data Warehousing and Mining Pub Date : 2023-11-28 DOI:10.4018/ijdwm.334024

Tao Chen, D. Luh, J. Wang

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引用次数: 0

Abstract

The study quantitatively examines how AI-generated cosmetic packaging design impact consumer satisfaction, offering strategies for database-driven development and design based on this evaluation. A comprehensive evaluation system consisting of 18 indicators in five dimensions was constructed by combining literature review and user interviews with expert opinions. On this basis, a questionnaire survey on AI-generated packaging design was conducted based on three types of datasets. In addition, importance-performance analysis was used to analyze the satisfaction of AI-generated packaging design indicators. The study found that while consumers are highly satisfied with the information transmission and creative attraction of AI-generated packaging design, the design's functional availability and user experience still have to be improved. It is suggested that the public model be combined into the data warehouse to build an AI packaging service platform. Focusing on the interpretability and controllability of the design process will also help increase consumer satisfaction and trust.

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用三种数据集分析人工智能生成的包装对消费者满意度的影响

本研究定量研究了人工智能生成的化妆品包装设计如何影响消费者满意度，并在此基础上提出了数据库驱动的开发和设计策略。研究结合文献综述、用户访谈和专家意见，构建了由五个维度 18 个指标组成的综合评价体系。在此基础上，基于三类数据集对人工智能生成的包装设计进行了问卷调查。此外，还采用重要性-绩效分析法对人工智能生成的包装设计指标的满意度进行了分析。研究发现，虽然消费者对人工智能生成包装设计的信息传递和创意吸引力满意度较高，但设计的功能可用性和用户体验仍有待提高。建议将公共模型纳入数据仓库，构建人工智能包装服务平台。注重设计过程的可解释性和可控性，也有助于提高消费者的满意度和信任度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving