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    <responseDate>2026-10-14T11:38:51Z</responseDate>
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    <identifier>10.57760/sciencedb.012rx</identifier>
    <datestamp>2026-09-23T19:49:33Z</datestamp>
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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:date>2026-09-23</dc:date>
  <dc:title>Experimental data on anthropomorphic AI customer service design, social presence, and user adoption intention: a 2 &amp;times; 2 between-subjects study (N = 305)</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.012rx</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This dataset contains the complete analysis data from a 2 &amp;times; 2 between-subjects experiment examining how the anthropomorphic design of AI customer-service agents influences users' use intention. A total of 305 participants were randomly assigned to one of four cells crossing visual anthropomorphism (high/low) and linguistic anthropomorphism (high/low), watched a 50-second simulated dialogue between a customer and the virtual service agent &amp;quot;Jiajia&amp;quot;, and then completed a questionnaire. The dataset comprises 305 rows &amp;times; 32 columns: five composite variables (visual anthropomorphism, linguistic anthropomorphism, social presence, use intention, and social anxiety, each computed as the arithmetic mean of its items), twenty Likert-scale measurement items (7-point anchors), experimental condition codes (scenario identifier plus two condition dummies), and three demographic variables (gender, age band, and education). There are no missing values. All direct and indirect identifiers &amp;mdash; including response ID, user ID, IP address, geolocation, timestamps, response duration, and distribution metadata &amp;mdash; were removed prior to deposition; only de-identified questionnaire responses and coarse demographic bands are retained. The dataset fully reproduces all results reported in the associated manuscript, including construct reliabilities (Cronbach's &amp;alpha;), the common method bias assessment (Harman's single-factor test), manipulation checks and the 2 &amp;times; 2 analysis of variance (with Levene's and Welch's robust tests), as well as mediation and moderated mediation analyses in which trait social anxiety moderates the social presence &amp;rarr; use intention path (5,000 bootstrap samples, bias-corrected confidence intervals). A full codebook and data-processing notes are provided in the &amp;quot;变量说明&amp;quot; (codebook) and &amp;quot;数据处理说明&amp;quot; (processing notes) worksheets of the deposited file.</dc:description>
  <dc:subject>AI customer service; anthropomorphism; social presence; social anxiety; use intention; moderated mediation</dc:subject>
  <dc:creator>Chen Yingsi</dc:creator>
  <dc:creator>Yu Xiaofeng</dc:creator>
  <dc:creator>Sun Jiaqian</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by-nc-nd/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
</oai_dc:dc>

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