{"title":"推进零售和服务战略:人工智能驱动的消费者行为预测、游戏化和道德营销","authors":"Minh Tung Tran","doi":"10.1016/j.jretconser.2025.104558","DOIUrl":null,"url":null,"abstract":"<div><div>This study addresses the research gap in understanding the combined effects of AI-driven predictive analytics on consumer personalization accuracy, engagement via gamification, and ethical governance in retailing and consumer services. The objective is to examine how predictive analytics enhances personalization and ROI, how gamification drives engagement, and how ethical challenges (e.g., privacy, bias) can be governed responsibly. Employing a convergent mixed-methods design, the study combines quantitative analysis of consumer data (n = 3900) with multi-case studies of Spotify, Netflix, and Amazon. Findings reveal that AI significantly improves personalization (<strong>β</strong> = 0.42, p < 0.001) and campaign ROI (<strong>R<sup>2</sup></strong> = 0.18), while gamification increases engagement by satisfying psychological needs. Ethical risk mitigation through frameworks such as the EU AI Act is demonstrated. Practical implications highlight actionable strategies for ethical AI adoption. Limitations include reliance on secondary qualitative sources and non-probability sampling; future research should explore probability samples and cross-cultural validation. This research contributes an integrated technical, psychological, and ethical framework, advancing theory on consumer trust and responsible innovation in retailing and consumer services.</div></div>","PeriodicalId":48399,"journal":{"name":"Journal of Retailing and Consumer Services","volume":"88 ","pages":"Article 104558"},"PeriodicalIF":13.1000,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advancing retail and service strategies: AI-driven consumer behavior prediction, gamification, and ethical marketing\",\"authors\":\"Minh Tung Tran\",\"doi\":\"10.1016/j.jretconser.2025.104558\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study addresses the research gap in understanding the combined effects of AI-driven predictive analytics on consumer personalization accuracy, engagement via gamification, and ethical governance in retailing and consumer services. The objective is to examine how predictive analytics enhances personalization and ROI, how gamification drives engagement, and how ethical challenges (e.g., privacy, bias) can be governed responsibly. Employing a convergent mixed-methods design, the study combines quantitative analysis of consumer data (n = 3900) with multi-case studies of Spotify, Netflix, and Amazon. Findings reveal that AI significantly improves personalization (<strong>β</strong> = 0.42, p < 0.001) and campaign ROI (<strong>R<sup>2</sup></strong> = 0.18), while gamification increases engagement by satisfying psychological needs. Ethical risk mitigation through frameworks such as the EU AI Act is demonstrated. Practical implications highlight actionable strategies for ethical AI adoption. Limitations include reliance on secondary qualitative sources and non-probability sampling; future research should explore probability samples and cross-cultural validation. This research contributes an integrated technical, psychological, and ethical framework, advancing theory on consumer trust and responsible innovation in retailing and consumer services.</div></div>\",\"PeriodicalId\":48399,\"journal\":{\"name\":\"Journal of Retailing and Consumer Services\",\"volume\":\"88 \",\"pages\":\"Article 104558\"},\"PeriodicalIF\":13.1000,\"publicationDate\":\"2025-10-02\",\"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/S0969698925003376\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Retailing and Consumer Services","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0969698925003376","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
摘要
本研究解决了在理解人工智能驱动的预测分析对消费者个性化准确性、游戏化参与度以及零售和消费者服务中的道德治理的综合影响方面的研究空白。我们的目标是研究预测分析如何提高个性化和投资回报率,游戏化如何推动用户粘性,以及如何负责任地管理道德挑战(如隐私,偏见)。该研究采用融合混合方法设计,将消费者数据(n = 3900)的定量分析与Spotify、Netflix和亚马逊的多案例研究相结合。研究结果显示,人工智能显著提高了个性化(β = 0.42, p < 0.001)和活动投资回报率(R2 = 0.18),而游戏化通过满足心理需求来提高用户粘性。展示了通过《欧盟人工智能法案》等框架减轻道德风险的情况。实际意义突出了道德人工智能采用的可操作策略。局限性包括依赖于二次定性来源和非概率抽样;未来的研究应探索概率样本和跨文化验证。本研究提供了一个综合的技术、心理和伦理框架,推进了零售和消费者服务中消费者信任和负责任创新的理论。
Advancing retail and service strategies: AI-driven consumer behavior prediction, gamification, and ethical marketing
This study addresses the research gap in understanding the combined effects of AI-driven predictive analytics on consumer personalization accuracy, engagement via gamification, and ethical governance in retailing and consumer services. The objective is to examine how predictive analytics enhances personalization and ROI, how gamification drives engagement, and how ethical challenges (e.g., privacy, bias) can be governed responsibly. Employing a convergent mixed-methods design, the study combines quantitative analysis of consumer data (n = 3900) with multi-case studies of Spotify, Netflix, and Amazon. Findings reveal that AI significantly improves personalization (β = 0.42, p < 0.001) and campaign ROI (R2 = 0.18), while gamification increases engagement by satisfying psychological needs. Ethical risk mitigation through frameworks such as the EU AI Act is demonstrated. Practical implications highlight actionable strategies for ethical AI adoption. Limitations include reliance on secondary qualitative sources and non-probability sampling; future research should explore probability samples and cross-cultural validation. This research contributes an integrated technical, psychological, and ethical framework, advancing theory on consumer trust and responsible innovation in retailing and consumer services.
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.