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The Impact of Anthropomorphism on Customer Satisfaction in Chatbot Commerce: An Experimental Study in the Food Sector

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Klein, Katharina, Martinez, Luis F.·2023·Electronic Commerce Research
DOI 10.1007/s10660-022-09562-8PMC PMC9108695
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Crossref · 10.1007/s10660-022-09562-8

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  • The empirical research on the effects of agentic commerce is still dispersed but suggests an interrelated set of commerce and psychological effects.

    “The empirical research on the effects of agentic commerce is still dispersed but suggests an interrelated set of commerce and psychological effects”

    From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [7]

    The Introduction (page unavailable) says empirical research on anthropomorphic chatbots in food e-commerce is limited. The Discussion (page unavailable) links chatbot design to enjoyment, attitude, trust, and customer satisfaction. These passages support a related set of psychological and commerce outcomes, but they do not establish that empirical research on agentic commerce generally is dispersed. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Design and channel factors (voice vs. text; initiation mode; anthropomorphic cues) influence perceived control and social presence, occasionally altering the direction of effects through reactance or satisfaction mechanisms.

    “Fourth, design and channel factors (voice vs. text; initiation mode; anthropomorphic cues) influence perceived control and social presence, occasionally altering the direction of effects through reactance or satisfaction mechanisms [7,24,31,32,52].”

    From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [7]

    The Literature review > Anthropomorphism (page not provided) says anthropomorphic design cues precede social presence, and the Discussion (page not provided) reports higher customer satisfaction with an anthropomorphic chatbot. The paper does not establish effects of voice versus text or initiation mode, changes in perceived control, or reversals of effect through reactance. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Lab experiments often manipulate assistant design or autonomy but measure intentions or simulated choice instead of actual checkout/payment.

    “For instance, lab experiments often manipulate the design of the assistant or give them more freedom, but they measure the results as intentions or simulated choice instead of actual checkout/payment [7,8,24,38,43,52,54,63].”

    From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [7]

    The Method (Research approach) describes an experiment comparing chatbots with and without anthropomorphic design features. The Method (Measurement) says it measured satisfaction, enjoyment, trust, and attitude—not intentions or simulated choice. The Discussion (Limitations and future research) confirms that the e-store stopped at the shopping cart and had no checkout process. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Panels are often not random samples, and the range of topics they cover can be very limited, such as one product category, one platform, or a few task types.

    “Panels are often not random samples, and the range of topics they cover can be very limited (for example, just one product category, one platform, or a few types of tasks) [7,8,41].”

    From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [7]

    The Method (Data collection and sample) describes non-probability convenience and snowball sampling. The Discussion (Limitations and future research) says the experiment was limited to food products and used a restricted e-store scenario. These passages support this study as an example of a non-random sample and narrow scope, but do not establish that panels are often like this. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • Numerous studies exhibit robust internal validity while functioning within simulated purchasing contexts.

    “Numerous studies exhibit robust internal validity while functioning within simulated purchasing contexts [7,8,24,63].”

    From From Recommendations to Delegation: A Systematic Review Mapping Agentic AI in E-Commerce and Its Consumer Effects (2026) · cites this paper as [7]

    The Method (Data collection and sample; page unavailable) says participants were randomly assigned to two chatbot scenarios. The Discussion (Limitations and future research; page unavailable) describes an experimental e-store with no full checkout, supporting the simulated-purchasing part. The paper does not establish robust internal validity; it notes that the scenario was recognizable as an experiment and may have biased respondents. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Klein, K., & Martinez, L. F.
Affiliations
NOVA School of Business and Economics (PT)
Corresponding author
Klein, Katharina
ORCID
Venue
Electronic Commerce Research
Publisher
Springer Science and Business Media LLC
Published
2022-05-16
Volume
23
Issue
4
Pages
2789-2825
ISSN
  • 1389-5753 (ISSN-L)
  • 1572-9362
DOI
10.1007/s10660-022-09562-8
PMC
PMC9108695
OpenAlex
W4280622019
Cited by
180
References
12
Citations by year
2026: 47 · 2025: 76 · 2024: 35 · 2023: 20 · 2022: 2
FWCI
10.94
Type
journal article
Language
en
Open access
Licence
Locations
  • Electronic Commerce Research (publishedVersion)
  • PubMed Central (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
Keywords
anthropomorphism, chatbots, customer satisfaction, food e-commerce, food retailers, consumer trust, consumer enjoyment, consumer attitudes, omnichannel strategy, chatbot design

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