当AI遇到影响者:AI驱动的instagram影响者推动消费者购买意愿的作用:SMIV和SOR框架的整合

Q1 Economics, Econometrics and Finance
Rohit Dhiman , Narender Singh Bhati
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引用次数: 0

摘要

人工智能(AI)已经成为Instagram网红们的游戏规则改变者。人工智能通过提供对最新趋势的洞察来帮助影响者完善他们的属性,并使影响者能够创建量身定制的内容,从而在深刻的层面上吸引受众。尽管有了这些进步,消费者还是陷入了信任错误影响者的陷阱,这对他们识别和信任正确的影响者构成了重大挑战。因此,本研究通过整合社交媒体影响者价值(SMIV)和刺激-有机体-反应(SOR)模型,利用目的抽样和滚雪球抽样收集了391个回答,考察了人工智能驱动的Instagram影响者属性对消费者购买意愿的影响。使用Smart-PLS 4.0的偏最小二乘-结构方程模型(PLS-SEM)对实证数据进行分析。研究结果强调,互动和可信度是影响品牌帖子的品牌意识和信任的最重要因素,而品牌意识和信任反过来又影响购买意愿。这项研究将使品牌、商业公司、Instagram网红以及最重要的消费者受益,以确定推动PI的最重要的人工智能Instagram网红属性。虽然这项研究的产出仅限于Instagram,主要集中在印度北部,但建议对其他社交媒体平台具有重要意义,并适用于全球。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
When AI meets influencers: Role of AI-powered instagram influencers driving consumers’ purchase intentions: An integration of SMIV & SOR framework
Artificial intelligence (AI) has become a game changer for Instagram influencers. AI assists influencers in refining their attributes by providing insights into the latest trends and enables influencers to create tailored content that engages audiences at a profound level. Despite such advancements, consumers fall into the trap of trusting the wrong influencer, posing a significant challenge for them to identify and trust the right influencer. Therefore, this study examines the Impact of AI-powered Instagram influencer attributes on consumers’ purchase intentions by integrating the Social Media Influencer Value (SMIV) and Stimulus-Organism-Response (SOR) models with 391 responses collected using purposive and snowball sampling. The empirical data were analyzed using Partial Least Squares-Structural Equation Modelling (PLS-SEM) using Smart-PLS 4.0. The findings highlighted that both Interaction and Trustworthiness were the most significant factors impacting Brand Awareness and Trust in Branded Posts, which in turn affect Purchase Intention (PI). This study will benefit brands, business firms, Instagram influencers, and most importantly the consumers in determining the most essential AI-powered Instagram influencer’s attributes that drive PI. While the output of this study is confined to Instagram and primarily focused on northern India, the recommendations hold significance for other social media platforms and are applicable worldwide.
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来源期刊
Journal of Open Innovation: Technology, Market, and Complexity
Journal of Open Innovation: Technology, Market, and Complexity Economics, Econometrics and Finance-Economics, Econometrics and Finance (all)
CiteScore
11.00
自引率
0.00%
发文量
196
审稿时长
1 day
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