人工智能助手感知真实性的分析建模:PLS-预测算法和重要性-性能图分析的应用

Palima Pandey, Alok Kumar Rai
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引用次数: 0

摘要

目的 本研究旨在探索人工智能(AI)助手感知真实性的后果,并开发一个序列中介架构,明确人与人工智能关系中忠诚度的因果关系。研究旨在评估基于训练-保留样本程序所开发模型的预测能力。设计/方法/途径基于引导技术的部分最小二乘结构方程模型(PLS-SEM)被用来检验与人机交互关系错综复杂性相关的高阶效应。研究样本包括 412 名属于千禧一代的人工智能助手用户。研究结果在 "感知真实性 "和 "忠诚度 "之间发现了正向关系,而在人与人工智能关系中,"感知质量 "和 "动物性 "对这一关系起到了序列中介作用。忠诚度 "仍然是 "情感依恋 "和 "口碑 "的重要预测因子。该模型具有很高的预测能力。图谱分析得出了相互矛盾的结果,表明 "真实性 "对 "忠诚度 "的预测作用最大,但对绩效维度的预测作用最小。它在二维地图上对忠诚度的预测因素进行了专门的相对评估。
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Analytical modeling of perceived authenticity in AI assistants: application of PLS-predict algorithm and importance-performance map analysis

Purpose

The present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship.

Design/methodology/approach

Partial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map.

Findings

A positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension.

Practical implications

The findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies.

Originality/value

The study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map.

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来源期刊
CiteScore
6.30
自引率
8.30%
发文量
18
期刊最新文献
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