The importance of individual difference : examining anthropomorphic tendency and responses to spokes-characters
Bibliographic record
Abstract
Anthropomorphism is a cognitive bias, which occurs when individuals see human characteristics in a non-human agent, object or animal. Anthropomorphism is especially interesting to marketers, because once anthropomorphic bias has been triggered, it can lead to a greater feeling of connectedness to a non-human agent (Tam, Lee and Chao, 2013), the emulation of behaviours (Aggarwal and McGill, 2012) or greater attribution of brand personality and brand liking (Delbaere, McQuarrie and Phillips, 2011). Importantly, research now shows that levels of this tendency vary between individuals (Waytz, Cacioppo and Epley, 2010), but research to date has failed to focus on how anthropomorphic tendency influences individual responses to marketing communications messages. Spokes-characters present an ideal context through which to examine this gap, given that they function as personified brands, designed to trigger consumer anthropomorphic tendency. Further, little is understood about how spokes-characters operate and which consumers will prefer them to their human counterparts. Like anthropomorphic research, much empirical work to date has focused on design and outcomes, examining the sender’s encoding process and the feedback generated, but ignoring the individual decoding process that is so important to understanding individual differences and message effectiveness. The current research employs three experiments using an online survey with stimulus exposure to show that anthropomorphic tendency, personality similarity and spokes-character type all have relevance to the understanding of this complex relationship. Study one and two indicate that while a human spokesperson is still preferred by many, higher levels of anthropomorphic tendency increase likeability of cartoon spokes characters. Study three highlights the importance of personality similarity, which further increases likability. Additional analyses provide key findings concerning the nature of anthropomorphic tendency as an individual difference and trait. This research contributes to a greater understanding of anthropomorphism theory and fills existing gaps in the consumer psychology and marketing communications literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".