A 16-item unidimensional scale measuring consumer perceptions of the trustworthiness of virtual social influencers (VSIs) -- computer-generated or digitally altered digital personas used in brand endorsement and social media marketing. Developed using an algorithmic item generation approach (the Psychometric Item Generator, PIG) seeded with GPT-4-generated items and refined through expert panel validation, EFA (n = 400), CFA (n = 297), nomological validity testing (n = 306), and pre-registered predictive validity testing (n = 210). Trustworthiness is conceptualised as a cognitive assessment of a VSI's credibility, reliability, and integrity, distinguishing it from the affective construct of connectedness (see companion scale VSIC, ID 1892). Grounded in socio-technical systems theory, which frames VSI trustworthiness as shaped by the interplay of consistent messaging, transparent disclosure, and culturally resonant content. In nomological testing, trustworthiness significantly predicted authenticity perceptions (beta = .512) and truthful endorsement (beta = .742). In predictive validity testing, it was positively associated with intention to interact (beta = .404), but did not significantly predict recommendation intention, advice-following intention, or overall behavioral intentions -- suggesting trust establishes initial credibility but that emotional bonding (captured by VSIC) drives most downstream behavioral outcomes.
van Esch, P., Cui, Y., Arli, D., & Eskridge, B. (2026). Virtual social influencer scale development and validation: An algorithmic approach. Australasian Marketing Journal. Advance online publication. https://doi.org/10.1177/14413582261423028
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