Sinan Li , Xinmin Huang , Yunying Sheng , Kai Chen
{"title":"The interactive effect of recommendation subjects and message types on consumers' suboptimal food purchase intentions","authors":"Sinan Li , Xinmin Huang , Yunying Sheng , Kai Chen","doi":"10.1016/j.jretconser.2024.104200","DOIUrl":null,"url":null,"abstract":"<div><div>Purchasing suboptimal foods is an effective measure to reduce food waste, but there is still significant consumer resistance in purchasing decisions. Message interventions are widely adopted by retailers as a convenient, flexible, and cost-effective strategy. The interactive effect of recommendation subjects and message types on suboptimal food purchase intentions is investigated in this study employing a 2 (recommendation subjects: AI vs. human) × 2 (message types: fact-based vs. affect-based) between-subjects experimental framework. It has been discovered that AI recommenders enhance purchase intentions when delivering fact-based messages, whereas human recommenders are more effective when offering affect-based messages. Moreover, the mediating role of green identity is confirmed. The interactive effect between recommendation subjects and message types is moderated by scarcity cues, with fact-based messages being more effective when combined with long-term scarcity cues, while affect-based messages being more effective when combined with short-term scarcity cues. In this work, the application of \"algorithm appreciation effect\" and \"algorithm aversion effect\" is expanded to the study of suboptimal food purchase intentions. It proposes that providing consumers with specific types of messages from AI or human recommenders can increase their purchase intentions, thereby offering theoretical support and practical insights for retailers' message strategies in suboptimal food marketing.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"84 ","pages":"Article 104200"},"PeriodicalIF":11.0000,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Retailing and Consumer Services","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S096969892400496X","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Purchasing suboptimal foods is an effective measure to reduce food waste, but there is still significant consumer resistance in purchasing decisions. Message interventions are widely adopted by retailers as a convenient, flexible, and cost-effective strategy. The interactive effect of recommendation subjects and message types on suboptimal food purchase intentions is investigated in this study employing a 2 (recommendation subjects: AI vs. human) × 2 (message types: fact-based vs. affect-based) between-subjects experimental framework. It has been discovered that AI recommenders enhance purchase intentions when delivering fact-based messages, whereas human recommenders are more effective when offering affect-based messages. Moreover, the mediating role of green identity is confirmed. The interactive effect between recommendation subjects and message types is moderated by scarcity cues, with fact-based messages being more effective when combined with long-term scarcity cues, while affect-based messages being more effective when combined with short-term scarcity cues. In this work, the application of "algorithm appreciation effect" and "algorithm aversion effect" is expanded to the study of suboptimal food purchase intentions. It proposes that providing consumers with specific types of messages from AI or human recommenders can increase their purchase intentions, thereby offering theoretical support and practical insights for retailers' message strategies in suboptimal food marketing.
期刊介绍:
The Journal of Retailing and Consumer Services is a prominent publication that serves as a platform for international and interdisciplinary research and discussions in the constantly evolving fields of retailing and services studies. With a specific emphasis on consumer behavior and policy and managerial decisions, the journal aims to foster contributions from academics encompassing diverse disciplines. The primary areas covered by the journal are:
Retailing and the sale of goods
The provision of consumer services, including transportation, tourism, and leisure.