Authors: Jessica Krasnove, Zhihao Yu, Yanping Tu
Faculty Mentor: Yanping Tu
College: Warrington College of Business
This study explored the relationship between anonymity and consumers’ willingness to recommend a product. Current research proposed that participants are somewhat less inclined to recommend a product due to concerns about self-presentation. This study seeks to analyze the extent in which self-presentation concerns are mitigated when asked to share a sunscreen product anonymously or with their identity attached, given both a masculine and feminine-framed product. It was hypothesized that anonymity would increase the likelihood of participants recommending the gender-incongruent product while the likelihood of participants recommending the gender-congruent product would remain constant. Four-hundred three MTurk participants were randomly assigned to one of four conditions of the 2 x 2 survey instrument: (1) anonymous-congruent, (2) anonymous-incongruent, (3) identifiable-congruent, and (4) identifiable-incongruent. Using three-way ANOVA, the study found higher likeliness for female participants to share the product than male participants, as shown with the participant-gender main effect. Additionally, there was a marginally significant product-gender-congruity main effect where the gender-incongruent product had a higher probability of being shared. As demonstrated by the gender-incongruent product, where participants may have increased concerns about social image, anonymity plays a role in increasing recommendations of products on Facebook. However, this may not hold true for gender-congruent products.
VERY well done – excellent hypothesis, research and good presentation skills. You did very well – this was interesting to read and to watch! This is useful information and was a great topic to choose! Thank you.
Mark S. Long, MS
Director, UF Innovate | Incubation Services
Thank you so much, Mr. Long! I appreciate your feedback!
Hey Jessica, interesting research! I could see how information like this might benefit a company that is unsure of how they might choose to promote their product.
How did you select the people to participate in the survey? I see the distinction between men and women, but were there any other parameters/traits of the people you surveyed (i.e. age, social factors, income)?
Hi Joseph! That’s a great question.
We used Amazon Mechanical Turk (MTurk) to randomly gather participants for the study. We did gather information on the demographics of our participants, such as age, race, native language, and gender. This was more just to see who was filling out our survey, but we did not make conclusions based on that. The study focused on gender since that was one of the variables we manipulated. We created two sunscreen products: Beauty&Skin and Sweat ‘N Sport. Sweat ‘N Sport is marketed toward males and has masculine product features (i.e. sweat-resistance) while Beauty&Skin is marketed toward females and has feminine product features (i.e. skin wrinkle prevention). We wanted to see if people would be more likely to anonymously recommend the product marketed towards the opposite gender. They were randomly presented with one of the two products (Beauty&Skin or Sweat ‘N Sport). Whether or not the Facebook post recommendation showed “Recommended by a friend” or “Recommended by [Your Name]” was random as well.
We did have more traits that we considered. In the survey, after the participants were presented with the Facebook post image, we gave participants a free-response box and asked them why they were willing or unwilling to share the product. Based on this information, we categorized participants on their reasoning. Some participants were unwilling to share the post because they feel that others wouldn’t view them as trustworthy. Others were unwilling to share the post because they did not want to spam others or were afraid others would view them negatively. Some participants were very willing to share the post because they thought the product was attractive or believed in the reliability of the product’s features. Most participants fell into one or more of these categories, and we looked at these factors closely.
Well organized and easy to understand poster, good work! Your video further clarified the study and the results.
What did the participant demographics look like in terms of age group and female to male ratio?
Hi Alexandra! Thank you so much for your comment.
We had participants who were 19 years old up to people who were 74 years old, so there was a large age range. Approximately 43% of the 403 participants were female, and approximately 57% of participants were male.
Very interesting poster! As for the demographics, do you think the results would differ between different demographics groups, such as different generations, socio-economic backgrounds, etc.?
Would you mind explaining what the “participant-gender” main effect means and how it shows that female participants were more likely to share (recommend?) a product?
Thanks, Nick
Very great research! Have you considered expanding your research to include influences of other demographics, for instance socio-economic status, ethnicity, etc…?