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The impact of generative AI shopping assistants on E-commerce consumer motivation and behavior: Consumer-AI interaction design 生成式人工智能购物助手对电子商务消费者动机和行为的影响:消费者-人工智能交互设计
IF 27 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2026-02-01 Epub Date: 2025-10-03 DOI: 10.1016/j.ijinfomgt.2025.102983
Guanghong Xie
Generative AI (Gen AI) shopping assistants have been extensively studied—both theoretically and empirically—for their impact on consumer experiences in developed-country e-commerce platforms. However, cultural, economic, and technological differences may constrain applicability in developing-country contexts. This study examines both the “lights and shadows” of Gen AI shopping assistants in developing countries, focusing on how these assistants shape the consumer motivation–behaviour process. We conduct a review from the perspectives of human–computer interaction (HCI), cognitive psychology, and marketing to assess the current state and challenges of Gen AI shopping assistants. Based on this review, we have developed the Motivation–Expectation Management Model (MEMM) to complete the following cycle: Motivation → HCI → Expectation Confirmation → Satisfaction and Repurchase → (feedback to) Motivation. We then collect data from consumers using the “Taobao Wenwen” Gen AI shopping assistant within the Taobao app in China and employ a mixed-methods approach to test the significance, importance, and necessity of the MEMM. (1) Extrinsic motivation exerts a greater influence on personalzation and UX than intrinsic motivation; (2) Mediation chains linking user experience, expectation confirmation, satisfaction, and repurchase intention are significant, with some relationships supported across significance, importance, and necessity analyses, while others are only partially consistent. In summary, MEMM provides both theoretical and empirical grounding for studying Gen AI shopping assistants in developing-country contexts, helps elucidate the consumer–Gen AI interaction mechanisms at play, and offers strategic guidance for sustaining a continuous cycle of interaction optimisation in e-commerce markets.
生成式人工智能(Gen AI)购物助手在发达国家的电子商务平台上对消费者体验的影响已经得到了广泛的理论和实证研究。然而,文化、经济和技术差异可能会限制在发展中国家的适用性。本研究考察了发展中国家人工智能购物助手的“光与影”,重点关注这些助手如何塑造消费者的动机-行为过程。我们从人机交互(HCI)、认知心理学和市场营销的角度进行综述,以评估人工智能购物助理的现状和挑战。在此基础上,我们建立了动机-期望管理模型(MEMM),以完成以下循环:动机→HCI→期望确认→满意度和再购买→(反馈)动机。然后,我们在中国使用淘宝应用程序中的“淘宝文文”代人工智能购物助手收集消费者数据,并采用混合方法来测试MEMM的重要性,重要性和必要性。(1)外在动机对个性化和用户体验的影响大于内在动机;(2)用户体验、期望确认、满意度和再购买意愿之间的中介链显著,显著性、重要性和必要性分析均支持部分关系,而其他关系仅部分一致。综上所述,MEMM为在发展中国家背景下研究人工智能购物助理提供了理论和实证基础,有助于阐明消费者-人工智能互动机制,并为在电子商务市场中维持持续的互动优化循环提供了战略指导。
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引用次数: 0
The literacy paradox: How AI literacy amplifies biases in evaluating AI-generated news articles 识字悖论:人工智能识字如何放大评估人工智能生成的新闻文章的偏见
IF 27 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2026-02-01 Epub Date: 2025-11-01 DOI: 10.1016/j.ijinfomgt.2025.102992
WooJin Kim , Yuhosua Ryoo
As Artificial Intelligence (AI) increasingly generates online news, AI literacy is promoted as essential for recognizing misinformation and bias. However, little is known about how AI literacy itself shapes biased processing. Across scenario-based and interactive AI news chatbot studies, we show that higher AI literacy can intensify opposing biases. When individuals better understand the use of AI in creating data-driven articles, they exhibit automation bias, perceiving AI as more objective and accurate, which in turn leads them to evaluate such articles as more credible. Conversely, when AI generates opinion- or emotion-based articles, high literacy fosters algorithmic aversion, perceiving AI as emotionless and context-blind, thereby evaluating these articles as less credible. These findings reveal a paradox: AI literacy, while intended to foster critical thinking, can instead heighten heuristic judgments, amplifying polarized perceptions of AI-generated news depending on content type.
随着人工智能(AI)越来越多地产生在线新闻,人工智能素养被认为是识别错误信息和偏见的关键。然而,人们对人工智能读写能力本身如何影响偏见处理知之甚少。通过基于场景和交互式人工智能新闻聊天机器人的研究,我们表明,更高的人工智能素养可能会加剧对立的偏见。当个人更好地理解人工智能在创建数据驱动文章中的使用时,他们会表现出自动化偏见,认为人工智能更客观、更准确,这反过来又会导致他们评估这些文章更可信。相反,当人工智能生成基于观点或情感的文章时,高识字率会培养对算法的厌恶,认为人工智能没有情感和上下文盲,从而评估这些文章的可信度较低。这些发现揭示了一个悖论:人工智能素养虽然旨在培养批判性思维,但却可以增强启发式判断,放大对人工智能生成的新闻的两极分化看法,这取决于内容类型。
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引用次数: 0
Technology mediated routines and their effects on organizational performance: An integrated affordance theoretic approach 技术介导的日常行为及其对组织绩效的影响:一种综合支持理论方法
IF 27 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2026-02-01 Epub Date: 2025-08-29 DOI: 10.1016/j.ijinfomgt.2025.102964
Dung Tien Nguyen , Onook Oh , Ronald Ramirez , Keith Guzik , Tony W. Tong
This study addresses a critical gap in Information Systems (IS) research that applies affordance theory. While previous IS affordance research has examined how technological affordance influences organizational routines or directly impacts performance, few studies have integrated these perspectives to explore how technology-induced routine changes mediate the relationship between technological affordances and organizational performance. To fill this gap, we first built an integrated affordance theoretic model. To validate this model, we collected survey data from 338 U.S. police departments focusing on using body-worn cameras (BWC) in their daily operation. Analyzing the survey data, we empirically validated that the technical affordances of BWCs (e.g., recording capabilities and infrastructural capabilities) drive changes in policing routines, which, in turn, enhance organizational performance. A primary contribution of this research is that we integrate qualitative and quantitative perspectives developed surrounding affordance theory in the IS research community, and validate the important role of routine changes in mediating the relationship between technological affordance and organizational performance. Our findings demonstrate that these technology-induced routine changes serve as key mediators, which exert a significant impact on performance beyond technology alone. This study underscores the importance of aligning technological affordance with organizational routines to drive sustainable improvements in organizational performance.
本研究解决了信息系统(IS)研究中应用信息性理论的一个关键空白。虽然以前的信息系统供给研究考察了技术供给如何影响组织常规或直接影响绩效,但很少有研究将这些观点整合起来,探索技术诱导的常规变化如何调解技术供给与组织绩效之间的关系。为了填补这一空白,我们首先建立了一个集成的功能理论模型。为了验证这个模型,我们收集了338 美国的调查数据警察部门在日常工作中重点使用穿戴式摄像机。通过对调查数据的分析,我们从经验上验证了bwc的技术能力(例如,记录能力和基础设施能力)推动了警务流程的变化,从而提高了组织绩效。本研究的一个主要贡献是,我们整合了信息系统研究界围绕服务性理论发展的定性和定量观点,并验证了常规变化在中介技术服务性与组织绩效之间的关系中的重要作用。我们的研究结果表明,这些技术引起的日常变化是关键的中介,它对绩效产生重大影响,而不仅仅是技术。这项研究强调了将技术支持与组织惯例相结合的重要性,以推动组织绩效的可持续改进。
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引用次数: 0
AI-powered CRM capability model: Advancing marketing ambidexterity, profitability and competitive performance 人工智能驱动的CRM能力模型:推进营销的双重性、盈利能力和竞争绩效
IF 27 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2026-02-01 Epub Date: 2025-10-01 DOI: 10.1016/j.ijinfomgt.2025.102981
Khadija Khamis Alnofeli , Shahriar Akter , Venkata Yanamandram , Umme Hani
The rapid adoption of Artificial Intelligence (AI)–powered Customer Relationship Management (CRM) systems has exposed a critical gap: despite substantial investment, many organisations fail to derive meaningful business value from these technologies. Recent surveys show that while AI is a strategic priority for executives, only a fraction report significant returns, with adoption challenges particularly acute in customer-facing functions. This study addresses this gap by conceptualising and empirically examining AI-powered CRM as a higher-order organisational capability. Drawing on the microfoundations of dynamic capability theory, we adopt a three-stage research design. First, a systematic scoping review and in-depth interviews with industry experts identify the core dimensions and subdimensions of AI-powered CRM capability. Second, we operationalise and validate these dimensions within a nomological network. Third, a survey of 205 banking employees in Australia tests the influence of AI-powered CRM capability on marketing ambidexterity and, in turn, on organisational outcomes. The quantitative analysis confirms that AI-powered CRM capabilities positively shape marketing ambidexterity, which subsequently enhances profitability and competitive advantage. Theoretically, the findings advance CRM research by introducing a microfoundational capability model that integrates data management, multi-channel integration, and service offerings. Practically, the study provides actionable guidance for managers seeking to close the “value realisation gap” by cultivating AI-powered CRM systems as dynamic capabilities that balance exploration and exploitation in volatile markets.
人工智能(AI)驱动的客户关系管理(CRM)系统的迅速采用暴露了一个关键的差距:尽管投入了大量资金,但许多组织未能从这些技术中获得有意义的商业价值。最近的调查显示,虽然人工智能是高管们的战略重点,但只有一小部分表示获得了可观的回报,在面向客户的职能部门,采用人工智能面临的挑战尤其严峻。本研究通过概念化和实证研究人工智能驱动的CRM作为一种高阶组织能力来解决这一差距。借鉴动态能力理论的微观基础,采用三阶段研究设计。首先,系统的范围审查和与行业专家的深入访谈确定了人工智能驱动的CRM能力的核心维度和子维度。其次,我们在一个逻辑网络中操作和验证这些维度。第三,一项针对澳大利亚205名银行员工的调查测试了人工智能驱动的CRM能力对营销双重性的影响,进而对组织成果的影响。定量分析证实,人工智能驱动的CRM能力积极塑造了营销的双重性,从而提高了盈利能力和竞争优势。从理论上讲,这些发现通过引入集成了数据管理、多渠道集成和服务产品的微基础能力模型,推进了CRM研究。实际上,该研究为寻求缩小“价值实现差距”的管理人员提供了可操作的指导,通过培养人工智能驱动的CRM系统作为动态能力,在动荡的市场中平衡探索和开发。
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引用次数: 0
Play the game then forever can begin: Designing games to extend gameplay 玩完游戏就永远可以开始了:设计游戏来扩展游戏玩法
IF 27 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2026-02-01 Epub Date: 2025-10-28 DOI: 10.1016/j.ijinfomgt.2025.102991
Gen-Yih Liao , Tzu-Ling Huang , Hsin-Yu Hung , Alan R. Dennis , Ching-I. Teng
Online games are among the most popular digital information systems for entertainment. Game providers frequently encounter the problem of retaining players. Players’ expressed interest in gameplay may not always be transformed into persistent gameplay behavior, posing challenges for game providers to extend players’ actual gameplay. To address this problem, we introduce a new concept, gameplay extension (measured in terms of the number of months a player actually continues playing a game), and explore how game elements can be designed to enhance gameplay extension. Drawing on goal gradient theory, we also examined the possible interplay of game design with gaming skills to formulate gameplay extension. We tested our model using multiwave and multisource data, including psychological and system-captured gameplay data from 379 players. We found that the mechanism affordance positively affects goal progress and concentration. Interestingly, concentration has a stronger effect than does goal progress on gameplay extension. Moreover, our findings uniquely clarify the pathway through which role-playing affordance extends gameplay, particularly among low-skilled players. Overall, our model explained 41% of the variance in gameplay extension, demonstrating its practical relevance. We argue that the findings apply to player-concentrated games or gamified systems.
网络游戏是最受欢迎的娱乐数字信息系统之一。游戏供应商经常会遇到留住玩家的问题。玩家对游戏玩法表达的兴趣可能并不总是转化为持久的游戏行为,这给游戏提供商扩展玩家的实际游戏玩法带来了挑战。为了解决这个问题,我们引入了一个新概念,即玩法扩展(游戏邦注:以玩家持续玩游戏的月数为衡量标准),并探索了如何设计游戏元素来增强玩法扩展。利用目标梯度理论,我们还研究了游戏设计与游戏技能之间可能的相互作用,以形成游戏玩法扩展。我们使用多波和多源数据来测试我们的模型,包括来自379名玩家的心理和系统捕获的游戏玩法数据。研究发现,机制亲和性对目标进展和注意力集中有正向影响。有趣的是,专注比目标进程对玩法扩展的影响更大。此外,我们的发现独特地阐明了角色扮演功能扩展游戏玩法的途径,特别是在低技能玩家中。总的来说,我们的模型解释了游戏玩法扩展中41%的差异,证明了它的实际相关性。我们认为这些发现适用于以玩家为中心的游戏或游戏化系统。
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引用次数: 0
Group closeness effects on co-owned information sharing: A multilevel perspective 群体亲密度对共有信息共享的影响:一个多层次的视角
IF 27 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2026-02-01 Epub Date: 2025-09-16 DOI: 10.1016/j.ijinfomgt.2025.102977
Mingxin Zhang , Ofir Turel , Anne Zöll
Co-owned information contains personal details about multiple individuals, often nested within a social group. It is important to study the sharing of such information because its careless disclosure can violate the privacy of all co-owners. What makes such sharing decisions unique is that they are often conducted within a tight social context, the attributes of which can systematically affect the decisions of all individuals nested within the group. This necessitates multi-level theorizing and testing. Doing so, we theorize the impact of group closeness (a group-level attribute) on co-owned information sharing by the group members (individual-level reflections and behaviors). We tested our ideas through a deceptive procedure: ninety participants in 40 groups were asked to voluntarily share a co-owned photo of 2–3 group members, for algorithm training purposes (cover story). Hierarchical Linear Modeling revealed (1) the retained relevance of self-centered private information sharing motivators and deterrents in group contexts, and (2) a cross-level effect of group closeness: it weakened the negative effect of privacy concerns on actual co-owned information sharing. The findings underscore the role of social context in determining the potency of privacy concerns to drive the privacy behaviors of individuals nested within this context.
共同拥有的信息包含多个个体的个人详细信息,通常嵌套在一个社会群体中。研究这些信息的共享是很重要的,因为它的不小心披露可能侵犯所有共同所有者的隐私。这种共享决策的独特之处在于,它们通常是在紧密的社会背景下进行的,这种社会背景的属性可以系统地影响嵌套在群体中的所有个体的决策。这需要多层次的理论和测试。为此,我们将群体亲密度(群体层面属性)对群体成员共同拥有的信息共享(个人层面的反思和行为)的影响理论化。我们通过一个欺骗程序来测试我们的想法:40个小组中的90名参与者被要求自愿分享2-3名小组成员的共同拥有的照片,以进行算法训练(封面故事)。层次线性模型揭示了(1)以自我为中心的隐私信息共享激励因素和阻止因素在群体情境下的保留相关性;(2)群体亲密度的跨层次效应:它削弱了隐私关注对实际共有信息共享的负面影响。研究结果强调了社会环境在决定隐私关注的效力方面的作用,以驱动嵌套在该环境中的个人的隐私行为。
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引用次数: 0
Not just in, but how: Leading physicians’ engagement strategies and patients’ continuous use of online medical team services 不仅仅是在,而是如何:领导医生的参与策略和患者持续使用在线医疗团队服务
IF 27 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-12-01 Epub Date: 2025-08-04 DOI: 10.1016/j.ijinfomgt.2025.102963
Siqi Wang
Drawing on the signaling theory, this study investigates how the leading physicians’ two distinct engagement strategies, direct and indirect engagement, influence patients’ continuous use of online medical team (OMT) service. This study employs a mixed-methods design, using a qualitative study to support the development of hypotheses and identify additional signals that may serve as potential moderators while utilizing a quantitative approach to provide empirical examination. The findings reveal that leading physicians’ direct engagement positively predicts continuous use, while their indirect engagement is negatively associated with continuous use. The signal of OMT’s historical performance strengthens the effect of direct engagement on patient continuous use, yet it does not significantly moderate the relationship between indirect engagement and continuous use. The signal of OMT’s current performance has no significant moderating effect on either engagement strategy. The post hoc analysis shows that the leading physicians’ individual performance signal positively moderates the relationships between both direct and indirect engagement and patient continuous use. This study elucidates how leading physicians’ distinct engagement strategies serve as differential signaling mechanisms, resulting in divergent outcomes for patient continuous use. Furthermore, it highlights the interplay between these strategy-induced signals and other contextual cues within the OMT environment, collectively shaping patients’ decision-making.
基于信号传导理论,本研究探讨了主要医生的两种不同参与策略(直接参与和间接参与)如何影响患者对在线医疗团队(OMT)服务的持续使用。本研究采用混合方法设计,使用定性研究来支持假设的发展,并识别可能作为潜在调节因子的额外信号,同时利用定量方法提供实证检验。研究结果显示,主要医生的直接参与积极预测持续使用,而他们的间接参与与持续使用负相关。OMT历史表现的信号增强了直接参与对患者持续使用的影响,但对间接参与与持续使用的关系没有显著调节作用。OMT当前绩效信号对两种参与策略均无显著调节作用。事后分析表明,主要医生的个人绩效信号正向调节直接和间接参与与患者持续使用之间的关系。本研究阐明了主要医生的不同参与策略如何作为不同的信号机制,导致患者持续使用的不同结果。此外,它强调了这些策略诱导信号与OMT环境中其他上下文线索之间的相互作用,共同塑造了患者的决策。
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引用次数: 0
Addressing consumer needs: Effects of firms remediation strategies on satisfaction and brand usage intent in AI-powered voice assistant service failures 解决消费者需求:企业补救策略对人工智能语音助手服务失败的满意度和品牌使用意图的影响
IF 20.1 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-12-01 Epub Date: 2025-07-07 DOI: 10.1016/j.ijinfomgt.2025.102951
Shihui Li , Yongzhong Yang , Chunjia Han , Yi Sun , Razaz Waheeb Attar , Brij B. Gupta
With the accelerating integration of AI-powered voice assistants into daily consumer interactions, effectively managing AI-driven service failures has become paramount for maintaining consumer trust, satisfaction, and sustained brand engagement. Despite extensive research on traditional service recovery mechanisms, existing frameworks fall short in addressing the distinct and complex nature of AI-driven failures. Motivated by the lack of systematic frameworks tailored explicitly to AI voice assistant contexts, this study introduces an integrated analytical framework grounded in Consistency Theory and Situational Crisis Communication Theory (SCCT) to address customer needs through strategic service failure remediation. Utilizing a mixed-methods research design and analyzing 5894 consumer reviews, the study establishes a consistency relationship between service failures and remediation strategies. It delineates three innovative approaches to service recovery and examines their impact on consumer satisfaction and brand usage intent. The empirical findings reveal significant positive effects of strategically aligned recovery efforts on consumer satisfaction and brand usage intentions. By addressing the specialized nature of AI-driven failures, this research not only advances theoretical knowledge in AI service management but also provides actionable strategic guidance for businesses seeking to optimize consumer experiences and foster enduring customer relationships.
随着人工智能语音助手加速整合到日常消费者互动中,有效管理人工智能驱动的服务故障对于维持消费者信任、满意度和持续的品牌参与至关重要。尽管对传统服务恢复机制进行了广泛的研究,但现有框架在解决人工智能驱动的故障的独特和复杂性质方面存在不足。由于缺乏针对人工智能语音助手情境量身定制的系统框架,本研究引入了一个基于一致性理论和情境危机沟通理论(SCCT)的综合分析框架,通过战略性服务故障补救来解决客户需求。利用混合方法研究设计和分析5894个消费者评论,本研究建立了服务故障与补救策略之间的一致性关系。它描述了服务恢复的三种创新方法,并检查了它们对消费者满意度和品牌使用意图的影响。实证结果表明,战略协调的恢复努力对消费者满意度和品牌使用意愿有显著的正向影响。通过解决人工智能驱动故障的特殊性,本研究不仅推进了人工智能服务管理的理论知识,而且为寻求优化消费者体验和培养持久客户关系的企业提供了可操作的战略指导。
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引用次数: 0
Engaging bystanders in response to online trolling customer misbehavior through service organization response strategies 通过服务机构的响应策略,吸引旁观者来应对网络钓鱼客户的不当行为
IF 20.1 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-12-01 Epub Date: 2025-07-24 DOI: 10.1016/j.ijinfomgt.2025.102957
Aimee Riedel , Rory Mulcahy , Amanda Beatson , Byron Keating
Managing customer misbehavior is crucial. Yet research regarding the management and response towards one specific customer misbehavior type, online trolling, has not been thoroughly considered. Three studies, including a field study, online experiments and critical incident technique (n = 777) explored whether, and why, customers (bystanders) may come to the aid of a service organization being trolled. This research examines the impact of troll type (hypocriticize and aggress) and service response strategy (deny, diminish, and apology), on the appraisal process of bystanders and their subsequent engagement behaviors. Results show that bystanders are more likely to support a service organization that is a victim of a hypocriticize troll in an offline setting through repurchase intentions. The results also show that when the service organization is a victim of an aggress troll, they should employ a deny crisis communication strategy to gain online support from bystanders. When the service organization, however, is a victim of a hypocriticize troll, an apology crisis communication strategy should be used. Results further reveal that attribution and negative moral emotions act as key serial mediators. The nature of attribution and negative moral emotions are also shown to be weaker for service organizations with higher level of reputation.
管理客户的不当行为至关重要。然而,关于对一种特定的客户不当行为类型的管理和反应的研究,在线拖钓,还没有被彻底考虑。三项研究,包括实地研究、在线实验和关键事件技术(n = 777),探讨了客户(旁观者)是否会以及为什么会来帮助被钓鱼的服务机构。本研究考察了巨魔类型(伪善和攻击性)和服务反应策略(否认、贬低和道歉)对旁观者评价过程及其后续参与行为的影响。结果表明,旁观者更有可能通过回购意愿支持离线环境中伪善喷子受害者的服务机构。结果还表明,当服务机构成为攻击性巨魔的受害者时,他们应该采用否认危机沟通策略来获得旁观者的在线支持。但是,当服务机构成为伪善喷子的受害者时,就应该使用道歉危机沟通策略。结果进一步揭示归因和负性道德情绪是主要的串行中介。服务组织的声誉越高,其归因性质和负性道德情绪也越弱。
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引用次数: 0
The power of GenAI nudges: How generative AI shapes consumer empowerment and goal desirability GenAI推动的力量:生成人工智能如何塑造消费者的权力和目标的可取性
IF 27 1区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-12-01 Epub Date: 2025-07-31 DOI: 10.1016/j.ijinfomgt.2025.102955
Ana Paula Merenda Richarde , Diego Costa Pinto , Marlon Dalmoro , Paulo Henrique Muller Prado
Generative Artificial Intelligence (GenAI) is reshaping consumer interactions by offering personalized guidance that ranges from broad suggestions to narrow recommendations. Yet, little is known about how these interactions influence decision-making and consumer empowerment. This research investigates how distinct types of GenAI nudges (narrow vs. broad) shape goal desirability and, in turn, consumer empowerment. Drawing upon Construal Level Theory (CLT), Goal Pursuit Theory, and Nudging Theory, we examine whether narrow (vs. broad) GenAI nudges enhance consumers' sense of empowerment by increasing goal desirability. Three mixed-method studies (one qualitative and two experimental) reveal that narrow GenAI nudges significantly heighten goal desirability, leading to greater consumer empowerment and key behavioral outcomes, including satisfaction, repurchase intentions, and advocacy (net promoter score). These findings advance theoretical perspectives on GenAI as a nudge for consumer decision-making and offer practical insights for designing AI systems that effectively guide consumer decisions within structured choice architectures.
生成式人工智能(GenAI)通过提供从广泛建议到狭隘建议的个性化指导,正在重塑消费者互动。然而,人们对这些互动如何影响决策和消费者赋权知之甚少。本研究调查了不同类型的GenAI推动(狭义与广义)如何塑造目标的吸引力,进而影响消费者的权力。利用解释水平理论(CLT)、目标追求理论和推动理论,我们研究了狭义的(与广义的)基因推动是否通过增加目标的期望来增强消费者的赋权感。三项混合方法研究(一项定性研究和两项实验研究)表明,狭窄的GenAI推动显著提高了目标的可取性,从而导致更大的消费者赋权和关键行为结果,包括满意度、再购买意愿和宣传(净推荐值)。这些发现推进了GenAI作为推动消费者决策的理论视角,并为设计在结构化选择架构中有效指导消费者决策的人工智能系统提供了实践见解。
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引用次数: 0
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International Journal of Information Management
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