The present study used relational and predictive approaches to build on past literature examining humanlike animal attributes. From the relational approach, it examined how five humanlike attributes ascribed to animals (Attributes Questionnaire) relate to one another and to attitudes toward 21 uses of animals (Attitudes Toward the Use of Animals Scale). From the predictive approach, it examined the predictive power of human affection toward animals and human perception of animal minds for granting animals moral consideration; additionally, it analyzed the predictive power of humanlike animal attributes for willingness to become an ethical vegetarian or ethical vegan. These analyses focused specifically on gender differences. The author used SPSS and SmartPLS 3.0, a Partial Least Square tool, for statistical analyses. Results from 481 Spanish university students responding to online and pencil-and-paper questionnaires revealed overall moderate correlations between different humanlike attributes and low correlations between those attributes and animal uses. Affection toward animals and perception of animal minds were good predictors for moral consideration of animals, especially when all four attributes were aggregated in the model (R2 = 0.47; Q2 = 0.32). Humanlike animal attributes directly affected students’ intentions to become vegetarian and vegan but the explanatory power was weak in both cases (R2 < 0.19; Q2 < 0.15). The study also revealed significant gender differences. Among women, humanlike animal attributes were more closely interrelated, better correlated with a greater number of animal uses, and stronger drivers of the moral status of animals. However, data showed no significant gender differences for path strength of humanlike animal attributes on the willingness to become vegetarian or vegan. In sum, perceiving humanlike attributes in animals has ethical consequences, but its influence on the adoption of pro-animal attitudes and behavior are still unclear. More research is needed to explore and explain causal relationships between the aforementioned variables and to uncover how gender differences may affect them.
|Publisher||Taylor & Francis|
|Author Address||Department of Marketing, Comillas Pontifical University (ICADE), Hermanos de Pablo Street 35, Atico 28027, Madrid, Spain.firstname.lastname@example.org|
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