Eine interessante Studie hat untersucht, ob sich das Geschlecht bei Ebay auswirkt:
Gender inequality in contemporary U.S. society is a well-documented, widespread phenomenon. However, little is known about gender disparities in product markets. This study is the first to use actual market data to study the behavior of women and men as sellers and buyers and differences in market outcomes. We analyze a unique and large data set containing all eBay auction transactions of most popular products by private sellers between the years 2009 and 2012. Women sellers received a smaller number of bids and lower final prices than did equally qualified men sellers of the exact same product. On average, women sellers received about 80 cents for every dollar a man received when selling the identical new product and 97 cents when selling the same used product. These findings held even after controlling for the sentiments that appear in the text of the sellers’ listings. Nonetheless, it is worth noting that this gap varied by the type of the product being sold. As a policy, eBay does not reveal the gender of users. We attribute the price differences to the ability of buyers to discern the gender of the seller. We present results from an experiment that shows that people accurately identify the gender of sellers on the basis of typical information provided in postings. We supplement the analysis with an additional off-eBay experiment showing that, in a controlled setting, people are willing to pay less for money-value gift cards when they are sold by women rather than men.
Demnach würden also Männer bei neuen Produkt mehr bekommen, nämlich einen Dollar, während Frauen nur 80 Cent erhalten, bei gebrauchten erhalten Frauen fast das gleiche, nur 97 Cent für den männlichen Dollar.
Die Studie ist allerdings erheblicher Kritik ausgesetzt. Bereits die Bestimmung des Geschlechts ist dabei sehr schwierig:
In addition, the study has an Achilles heel. While the authors claim to know the gender of eBay sellers, they admit that most sellers don’t publicly identify their genders:
“Potential buyers do not receive direct information from eBay about the sellers’ gender. Yet, the gender of a private seller can be gleaned from the range of items a merchant is offering for sale (for example, selling female clothing suggests that the seller is likely a woman) and, at times, from the seller’s username.”
The authors want to attribute their findings to gender discrimination, but they can’t unless they can prove that buyers can figure out the gender of anonymous eBay sellers. So the authors are trying to claim that buyers routinely accurately guess the gender of a seller (again – assuming the selling actually has one gender).
“Four hundred people participated in the experiment, each evaluating five user profiles. Of the 2000 evaluations, the gender was correctly identified in 1127 cases and mistakenly identified in 170. In 701 cases, participants reported that they could not discern whether the sellers were male or female”
So 170 (mistaken gender) + 701 (could not discern) = 871 (couldn’t correctly guess gender). 871 (couldn’t correctly guess gender)/1127 (could correctly guess gender) = 56.35% chance can correctly guess gender
1127 (could correctly guess gender) + 170 (incorrectly guessed gender) = 1297 (could make any guess about gender)/2000 = 64.85% chance confident enough to make make any guess (true/false) about gender.
A 56.35% chance respondents could guess the correct gender and a 64.85% respondents felt confident enough to make any guess regarding gender. This doesn’t seem like a very convincing argument that buyers consistently guess a seller’s gender, especially when guessing gender is already only a 50% coin toss. Indeed, it shows that over one-third (100%-64.85%=35.15%) of the time a buyer doesn’t even feel confident enough to guess a seller’s gender. Also, none of this actually proves that actual buyers try to guess the gender of the seller or that it affects their bidding decisions.
Zudem sind auch andere Faktoren nicht gleich:
The study claims:
“Auctions are ideal for testing for gender differences in outcomes because, after an item has been listed, the final price is not affected by the seller’s behavior, only by the bidding of potential buyers.”
This is not true. There are numerous other variables that could affect a buyer’s bid: the sellers rating, the sellers return policy, the seller’s page layout, the product description, shipping fees, shipping location, warranties, pictures of the item, whether the buyer is currently bidding on competing items, time left in the auction, number of other bids, number of competing auctions currently available, etc.
These seem much more obvious and likely decisive factors than what gender a buyer thinks a seller might be. The study claims it controls for many (but not all) of these of possible factors, but I don’t see how they could possible effectively control for qualitative subjective variables such as the quality of a product photo or product description. They also don’t appear to include major factors like return policies or warranties.
Furthermore, the study finds that men and women tend to sell very different items. Women also tend to sell cheaper items and set lower starting bids. In addition, female sellers only make up only 23.07% of the sellers in the study’s dataset. So even more statistical voodoo is used to try to make data on male and female sellers comparable.
Wenn ich es richtig gelesen habe, dann haben die Männer den Startpreis 15% höher angesetzt und auch bei der Einstellung des Angebots doppelt so häufig Titel mit Fettdruck verwendet, 50% mehr Fotos eingestellt, wobei sie bei den Fotos 33% Prozent weniger „Stockfotos“, also Bilder, die anderweitig als bei dem konkreten Produkt erstellt worden sind, verwendet haben.
In der Studie wurden dann noch ein direkter Test gemacht, wie sich ein weiblicher oder männlicher Name auf den Verkauf von Gutscheinkarten auswirkt:
To test whether people evaluate products that women sell as less valuable than the same products when sold by men, we conducted another experiment on Amazon Mechanical Turk, asking participants to report the monetary value they assign to an Amazon $100 money-value gift card (“How much are you willing to pay?”) when sold by either Alison or Brad.
As shown in Fig. 2, the results of the experiment support the hypothesis that a lower value is assigned to products when sold by women than by men. One hundred sixteen people participated in the experiment; 59 were asked to report their evaluation of a $100 gift card sold by Alison, and 57 were asked to report their evaluation of a $100 gift card sold by Brad. The average value assigned to the gift card sold by a woman was $83.34, whereas the average value assigned to the same card sold by a man was $87.42 (P < 0.05; see table S10). Recall that similar differences in price between women and men sellers were found when we analyzed transactions of gift cards on eBay (Table 2). (The gender of the participants in the experiments did not affect the final price, nor did it affect the differences between the prices of gift cards sold by a woman and the prices of gift cards sold by a man.)
Hier die Daten von diesem Experiment:
Da scheint mir gleichzeitig die Streuung etwas höher zu sein bei den Frauen, die Teilnehmerzahl ist nicht sehr hoch, es wäre interessant, ob die Ergebnisse damit zusammenhängen könnten, dass da mehr Abweichungen nach oben und nach unten vorhanden waren und wie groß da die Bedeutung einzelner Angebote war.
Auch so gibt es recht wenig über das Experiment: Waren in beiden Gruppen gleich viele Männer und Frauen? Was für Gutscheine waren es? (wenn zB eine Frau einen Gutschein für einen Frauenuntypischen Bereich verkauft, dann könnte ein Käufer davon ausgehen, dass sie ihm einen geringeren Wert zuweist. Wie waren die Texte? Waren sie bei beiden gleich? Wie hätten sie mit anderen Namen abgeschnitten? Beschwört vielleicht Brad das Bild eines härteren Verhandlers herauf als ein anderer Männername?)