自建IP还是合作IP：虚拟影响者代言人选择策略对消费者融入的影响

doi:10.3724/SP.J.1042.2025.0965

摘要/Abstract

摘要：

虚拟影响者代言是依托人工智能技术赋能的新型品牌传播手段, 能够在社交媒体中发挥卓越的影响力。然而, 在如何有效利用虚拟影响者代言来驱动消费者融入方面, 企业面临着特殊的虚拟影响者代言人选择策略问题, 即在品牌自建虚拟影响者策略和与第三方虚拟影响者合作策略之间进行权衡。由此, 本文基于传播时间、传播精度、传播关系三方面研究视角, 分别提出传播时效机制(研究1)、信息分辨机制(研究2)、关系建立机制(研究3), 以期全面解析虚拟影响者代言人选择策略对消费者融入的影响; 同时, 还将进一步讨论人工智能技术因素和虚拟影响者/消费者因素的潜在调节作用。由此, 本文旨在填补过往研究对该策略问题分析的不足, 从而帮助推动虚拟影响者营销领域的研究, 并为业界提供有价值的管理启示。

关键词: 品牌代言, 虚拟影响者, 营销策略, 消费者融入, 人工智能营销

Abstract:

Virtual influencer endorsements, empowered by artificial intelligence technology, offer a new approach to brand communication and exert outstanding influence on social media platforms. However, research on the relationship between virtual influencer endorsements and consumer engagement remains in its early stages, not only limited in scope but also facing two primary research gaps. First, firms face a unique challenge in leveraging these endorsements to enhance consumer engagement. This challenge arises from a strategic tension in selecting either brand-developing proprietary virtual influencers or collaborating with third-party virtual influencers. However, there is a lack of exploration of the impact of virtual influencer endorsement selection strategies on consumer engagement. Second, existing literature has yet to investigate the underlying mechanisms and boundary conditions. From various theoretical perspectives, virtual influencer endorsement involves several key mechanisms, including the communication cycle, information processing, and relationship interaction. Therefore, understanding the effectiveness of these mechanisms is crucial for addressing the differing brand communication effects generated by different virtual influencer endorsement selection strategies.

In response to these research gaps, based on the communication time, accuracy, and relationships perspectives, this study proposes communication timeliness mechanisms (Study 1), information discrimination mechanisms (Study 2), and relationship-building mechanisms (Study 3) to comprehensively examine the effects and mechanisms of virtual influencer endorsement selection strategies (brand-developing proprietary versus collaborating with third-party) on consumer engagement, and explores key boundary conditions from artificial intelligence technology factors and virtual influencer/consumer factors perspectives, combined with brand communication-related theories and influencer marketing.

Specifically, first, drawing on the research insights on brand awareness in the process of brand communication in marketing, and based on the signal detection theory, this study aims to explore the communication time mechanism of long-term "brand awareness" and "virtual influencer awareness" induced by virtual influencer endorsements selection strategies, and further analyze the moderating effect of the artificial intelligence technology factor (i.e., authenticity level of virtual influencers) and influencer factor (i.e., brand-virtual influencer consistency) (Study 1). Second, grounded in the elaboration likelihood model (ELM), which is widely used in the advertising domain, this study aims to explore the double-edged sword information discrimination mechanism of advertising intrusiveness and information diagnostic induced by virtual influencer endorsements selection strategies selection and examine the moderating effect of artificial intelligence technology factor (i.e., authenticity level of virtual influencers) and consumer factor (i.e., need for cognition) (Study 2). By doing so, it comprehensively understands how consumers distinguish the endorsement information of virtual influencers. Third, following the widely used parasocial interaction theory in the field of social media marketing, this study explores the relationship-building mechanism of consumers in virtual influencer endorsement brand activities, that is, consumer-brand identification and consumer-virtual influencer identification, and examines the moderating effect of artificial intelligence technology factor (i.e., virtual influencer's agency: fully artificial intelligence-driven versus manual intervention) the authenticity level of virtual influencers and influencer factor (i.e., brand-virtual influencer consistency) (Study 3).

In response to these research gaps, this work makes the following contributions. First, this article focuses on the uniqueness of virtual influencer endorsement selection strategies, thus expanding the scope of brand endorsement research. While existing studies primarily explore the differences between virtual and real influencers in brand communication, few studies examine the specific selection strategies for virtual influencer endorsements. By analyzing this selection strategy, this study enriches the theoretical research system of brand endorsement and provides new topics for further research in this field. Additionally, this study systematically investigates the multiple mediation models, comprehensively revealing the underlying mechanisms, which contributes to understanding the relationship between virtual influencer endorsements selection strategies and consumer engagement and advancing virtual influencer marketing research. Furthermore, this study reveals the boundary conditions related to artificial intelligence technology factors (i.e., authenticity level of virtual influencers, virtual influencer's agency: fully artificial intelligence-driven versus manual intervention), virtual influencer factor (i.e., brand-virtual influencer consistency), and consumer factor (i.e., need for cognition), thereby facilitating interdisciplinary integration between the fields of influencer marketing, AI technology and psychology. Moreover, this study aims to offer effective guidance for firms in selecting virtual influencer spokespersons, managing interventions for virtual influencer applicability, and implementing artificial intelligence marketing, thereby providing crucial insights for virtual influencer practices.

Key words: brand endorsement, virtual influencer, marketing strategy, consumer engagement, artificial intelligence marketing

中图分类号:

B849: F317.55

项典典, 尹雨乐, 葛梦琦, 王子涵. (2025). 自建IP还是合作IP：虚拟影响者代言人选择策略对消费者融入的影响. 心理科学进展 , 33(6), 965-983.

XIANG Diandian, YIN Yule, GE Mengqi, WANG Zihan. (2025). The impact of brand-developing versus collaborative virtual influencer endorsement selection strategies on consumer engagement. Advances in Psychological Science, 33(6), 965-983.

图/表 3

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代表文献	术语	定义描述
Byun & Ahn, 2023; Kim & Baek, 2024; Mouritzen et al., 2024; Shen, 2024; Zhou, Yan et al., 2024	虚拟影响者 Virtual influencer	一类数字化实体, 具有拟人化的外观、类似真人的社会角色和独立的身份特质, 借助人工智能技术能够与其他人类在社交媒体中展开高质量互动, 其控制者可以是人类或算法。
Ham et al., 2023	虚拟品牌代言人 Virtual brand endorser	在社交媒体中拥有粉丝基础并能和粉丝互动, 旨在服务于品牌代言工作的一类虚拟数字人。
晏青,何丽敏, 2023; 朱华伟等, 2022	虚拟明星/偶像 Virtual celebrity/idol	具有人类、动物、拟人化生物等形象, 能够在计算机、互联网及人工智能技术搭建的场景中进行演艺活动(如歌手), 企业能够将其用于产品推广和品牌传播。
Baudier et al., 2023	社交媒体中的机器人影响者 Social media robot influencer	运用人工智能情感技术, 机器人影响者能够在社交媒体中识别、理解和表达情感, 以此增强它们与人类的互动效果, 从而服务于传递信息和建立关系的功能。
Sands, Campbell et al., 2022	人工智能影响者 Artificial intelligence (AI) influencers	依托机器学习技术驱动, 能与真人影响者一样在多个社交媒体的内容板块中生成内容; 其拥有多种不同类型的外观。
Chen & Hu, 2024	虚拟主播 Virtual uploader/Vtuber	通常拥有卡通外观, 主要在社交媒体中(如哔哩哔哩)进行各式各样的直播活动, 由真人穿戴设备并依托实时捕捉技术和虚拟直播系统来实现角色扮演。

代表文献	术语	定义描述
Byun & Ahn, 2023; Kim & Baek, 2024; Mouritzen et al., 2024; Shen, 2024; Zhou, Yan et al., 2024	虚拟影响者 Virtual influencer	一类数字化实体, 具有拟人化的外观、类似真人的社会角色和独立的身份特质, 借助人工智能技术能够与其他人类在社交媒体中展开高质量互动, 其控制者可以是人类或算法。
Ham et al., 2023	虚拟品牌代言人 Virtual brand endorser	在社交媒体中拥有粉丝基础并能和粉丝互动, 旨在服务于品牌代言工作的一类虚拟数字人。
晏青,何丽敏, 2023; 朱华伟等, 2022	虚拟明星/偶像 Virtual celebrity/idol	具有人类、动物、拟人化生物等形象, 能够在计算机、互联网及人工智能技术搭建的场景中进行演艺活动(如歌手), 企业能够将其用于产品推广和品牌传播。
Baudier et al., 2023	社交媒体中的机器人影响者 Social media robot influencer	运用人工智能情感技术, 机器人影响者能够在社交媒体中识别、理解和表达情感, 以此增强它们与人类的互动效果, 从而服务于传递信息和建立关系的功能。
Sands, Campbell et al., 2022	人工智能影响者 Artificial intelligence (AI) influencers	依托机器学习技术驱动, 能与真人影响者一样在多个社交媒体的内容板块中生成内容; 其拥有多种不同类型的外观。
Chen & Hu, 2024	虚拟主播 Virtual uploader/Vtuber	通常拥有卡通外观, 主要在社交媒体中(如哔哩哔哩)进行各式各样的直播活动, 由真人穿戴设备并依托实时捕捉技术和虚拟直播系统来实现角色扮演。

代表文献	关键机制检验	代言人选择策略研究	边界条件
脉络1：对虚拟影响者属性的分析
Kim & Park, 2023	吸引力→模仿欲望, 品牌依恋→购买意愿	×	产品类型的匹配
Li et al., 2023	拟人化(外表, 行为)→产品真实性, 产品关联性→代言态度	×	产品类型
El Hedhli et al., 2023	拟人化→温暖感知, 能力感知→采纳意愿, 购买意愿	×	×
Alboqami, 2023	吸引力(外表等), 可信度(真实性等), 一致性(影响者−产品/消费者)→信任	×	×
王颖等, 2024	真实性感知→虚拟依恋→旅游意愿	×	熟悉度; 代言人发展预期
脉络2：对虚拟影响者的比较分析
姜凌,冯源, 2020	虚拟影响者 vs. 真人影响者→积极情绪→广告说服力	×	独特需求
朱华伟等, 2022	虚拟影响者vs. 真人影响者→加工流畅性→购买意愿	×	创新产品类型(突破式vs. 渐进式)
Franke et al., 2023	虚拟影响者 vs. 真人影响者→专业性感知→广告态度, 购买意愿等	×	产品类型; 影响者类型披露
Ozdemir et al., 2023	虚拟影响者 vs. 真人影响者→可信度感知→品牌态度	×	语言类型(感性 vs.理性)
Sands, Campbell et al., 2022	虚拟影响者 vs. 真人影响者→心理距离→关注意愿, 口碑等	×	独特化需求; 影响者代理(自主 vs.管理)
Thomas & Fowler, 2021	虚拟影响者 vs. 真人影响者→责任感知→品牌态度, 购买意愿	×	×
Wang & Qiu, 2023	类人虚拟影响者 vs. 动漫虚拟影响者→感知社会价值→购买意愿	×	广告信息框架(防御型 vs. 促进型)
Zhou, Li et al., 2024	虚拟影响者 vs. 真人影响者→情感投入, 准社会关系→品牌代言有效性	×	帖子类型(视频 vs.图片)
Zhou, Yan et al., 2024	虚拟影响者 vs. 真人影响者→意象难度, 感官能力感知→购买意愿	×	感官体验
本文	虚拟影响者代言人选择策略(自建vs.合作)→传播时效机制、信息分辨机制、关系建立机制→消费者融入	√	人工智能技术因素, 虚拟影响者/消费者因素

代表文献	关键机制检验	代言人选择策略研究	边界条件
脉络1：对虚拟影响者属性的分析
Kim & Park, 2023	吸引力→模仿欲望, 品牌依恋→购买意愿	×	产品类型的匹配
Li et al., 2023	拟人化(外表, 行为)→产品真实性, 产品关联性→代言态度	×	产品类型
El Hedhli et al., 2023	拟人化→温暖感知, 能力感知→采纳意愿, 购买意愿	×	×
Alboqami, 2023	吸引力(外表等), 可信度(真实性等), 一致性(影响者−产品/消费者)→信任	×	×
王颖等, 2024	真实性感知→虚拟依恋→旅游意愿	×	熟悉度; 代言人发展预期
脉络2：对虚拟影响者的比较分析
姜凌,冯源, 2020	虚拟影响者 vs. 真人影响者→积极情绪→广告说服力	×	独特需求
朱华伟等, 2022	虚拟影响者vs. 真人影响者→加工流畅性→购买意愿	×	创新产品类型(突破式vs. 渐进式)
Franke et al., 2023	虚拟影响者 vs. 真人影响者→专业性感知→广告态度, 购买意愿等	×	产品类型; 影响者类型披露
Ozdemir et al., 2023	虚拟影响者 vs. 真人影响者→可信度感知→品牌态度	×	语言类型(感性 vs.理性)
Sands, Campbell et al., 2022	虚拟影响者 vs. 真人影响者→心理距离→关注意愿, 口碑等	×	独特化需求; 影响者代理(自主 vs.管理)
Thomas & Fowler, 2021	虚拟影响者 vs. 真人影响者→责任感知→品牌态度, 购买意愿	×	×
Wang & Qiu, 2023	类人虚拟影响者 vs. 动漫虚拟影响者→感知社会价值→购买意愿	×	广告信息框架(防御型 vs. 促进型)
Zhou, Li et al., 2024	虚拟影响者 vs. 真人影响者→情感投入, 准社会关系→品牌代言有效性	×	帖子类型(视频 vs.图片)
Zhou, Yan et al., 2024	虚拟影响者 vs. 真人影响者→意象难度, 感官能力感知→购买意愿	×	感官体验
本文	虚拟影响者代言人选择策略(自建vs.合作)→传播时效机制、信息分辨机制、关系建立机制→消费者融入	√	人工智能技术因素, 虚拟影响者/消费者因素