Behind the hype: a closer look at voice assistant skills, product control strategy and user evaluations

Purpose Drawing on the assemblage framework and signaling theory, this research examines how a voice skill's product control strategy, specifically controllability variety and complexity, shapes perceived intelligence and user evaluations. It also explores the invocation strategy (licensing vs. co-branding) as a boundary condition for these relationships. Design/methodology/approach A multi-source, multi-method approach is adopted, using field data from 481 Amazon Alexa skills, over 47,000 user reviews, two user surveys and expert-coded data. Hypotheses are tested using multiple analyses in SPSS. Findings Controllability variety functions as a competence signal and is positively associated with perceived intelligence. Controllability complexity serves as a friction signal and penalizes perceived intelligence. In turn, perceived intelligence acts as a primary driver of user evaluations. Moreover, an invocation license intensifies the negative complexity–perceived intelligence relationship more than co-branding invocation does. Originality/value This study shifts the research focus from platform-level voice assistants to their micro-level skills. It integrates signaling theory with the assemblage framework, establishing that voice skills function as a critical entity within a triadic user–AI–product assemblage. By introducing and empirically contrasting the invocation strategy, it provides a novel perspective on how the locus of artificial intelligence identity governs attribution within the assemblage and shapes user perceptions of intelligence.

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Publication Details

Journal
Marketing Intelligence & Planning
Published
2026-08-28
DOI
https://doi.org/10.1108/mip-10-2025-0782
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Behind the hype: a closer look at voice assistant skills, product control strategy and user evaluations

Yazhen Xiao, Haisu Zhang
Marketing Intelligence & Planning
AI in Service Interactions
article

Behind the hype: a closer look at voice assistant skills, product control strategy and user evaluations

Yazhen Xiao, Haisu Zhang
article en

Abstract

Purpose Drawing on the assemblage framework and signaling theory, this research examines how a voice skill's product control strategy, specifically controllability variety and complexity, shapes perceived intelligence and user evaluations. It also explores the invocation strategy (licensing vs. co-branding) as a boundary condition for these relationships. Design/methodology/approach A multi-source, multi-method approach is adopted, using field data from 481 Amazon Alexa skills, over 47,000 user reviews, two user surveys and expert-coded data. Hypotheses are tested using multiple analyses in SPSS. Findings Controllability variety functions as a competence signal and is positively associated with perceived intelligence. Controllability complexity serves as a friction signal and penalizes perceived intelligence. In turn, perceived intelligence acts as a primary driver of user evaluations. Moreover, an invocation license intensifies the negative complexity–perceived intelligence relationship more than co-branding invocation does. Originality/value This study shifts the research focus from platform-level voice assistants to their micro-level skills. It integrates signaling theory with the assemblage framework, establishing that voice skills function as a critical entity within a triadic user–AI–product assemblage. By introducing and empirically contrasting the invocation strategy, it provides a novel perspective on how the locus of artificial intelligence identity governs attribution within the assemblage and shapes user perceptions of intelligence.

Marketing Intelligence & Planning
New Jersey Institute of Technology (US), Portland State University (US)
Openalex Percentile: Top 8%
AI in Service Interactions
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Behind the hype: a closer look at voice assistant skills, product control strategy and user evaluations — Yazhen Xiao, Haisu Zhang · Marketing Intelligence & Planning (2026) | TGRS Research Map | TGRS