{"title":"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","authors":"Tao Chen, D. Luh, J. Wang","doi":"10.4018/ijdwm.334024","DOIUrl":null,"url":null,"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.","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analyzing AI-Generated Packaging's Impact on Consumer Satisfaction With Three Types of Datasets\",\"authors\":\"Tao Chen, D. Luh, J. Wang\",\"doi\":\"10.4018/ijdwm.334024\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":54963,\"journal\":{\"name\":\"International Journal of Data Warehousing and Mining\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2023-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Data Warehousing and Mining\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.4018/ijdwm.334024\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Warehousing and Mining","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.4018/ijdwm.334024","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Analyzing AI-Generated Packaging's Impact on Consumer Satisfaction With Three Types of Datasets
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.
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