Table 1.
Characteristics of Pokémon trading cards offered (n = 300) and sold (n = 220) on the e-commerce platform eBay during the study period. The total revenue achieved was 923.60 €.
Table 2.
Comparison of sales prices of Pokémon trading cards (n = 220) across different variables.
Fig 1.
Kaplan–Meier curves showing “survival” distributions of Pokémon trading cards offered on eBay (n = 300).
Survival time was defined as the time between offer and sale for sold cards, or as the time between offer and the end of the study period for unsold cards (reflecting censored data). Comparison of cards of different grades of rarity.
Fig 2.
Kaplan–Meier curves showing “survival” distributions of Pokémon trading cards offered on eBay (n = 300).
Survival time was defined as the time between offer and sale for sold cards, or as the time between offer and the end of the study period for unsold cards (reflecting censored data). Comparison of holofoil and matte cards.
Fig 3.
Kaplan–Meier curves showing “survival” distributions of Pokémon trading cards offered on eBay (n = 300).
Survival time was defined as the time between offer and sale for sold cards, or as the time between offer and the end of the study period for unsold cards (reflecting censored data). Comparison of cards in German language and non-German cards.
Fig 4.
Kaplan–Meier curves showing “survival” distributions of Pokémon trading cards offered on eBay (n = 300).
Survival time was defined as the time between offer and sale for sold cards, or as the time between offer and the end of the study period for unsold cards (reflecting censored data). Comparison of cards from nine different sets.
Fig 5.
Kaplan–Meier curves showing “survival” distributions of Pokémon trading cards offered on eBay (n = 300).
Survival time was defined as the time between offer and sale for sold cards, or as the time between offer and the end of the study period for unsold cards (reflecting censored data). Pairwise log-rank tests with adjustments for multiple testing revealed two significantly different survival distributions: Base Set 2 vs. Team Rocket (shown here), and Base Set 2 vs. Black Star Promo (shown in Fig 6).
Fig 6.
Kaplan–Meier curves showing “survival” distributions of Pokémon trading cards offered on eBay (n = 300).
Survival time was defined as the time between offer and sale for sold cards, or as the time between offer and the end of the study period for unsold cards (reflecting censored data). Pairwise log-rank tests with adjustments for multiple testing revealed two significantly different survival distributions: Base Set 2 vs. Team Rocket (shown in Fig 5), and Base Set 2 vs. Black Star Promo (shown here). Of note, only one Black Star Promo card was contained in the sample, suggesting that this result should be interpreted with caution.
Fig 7.
Kaplan–Meier curves showing “survival” distributions of Pokémon trading cards offered on eBay (n = 300).
Survival time was defined as the time between offer and sale for sold cards, or as the time between offer and the end of the study period for unsold cards (reflecting censored data). Cox regression analysis additionally indicated an increased hazard ratio (i.e., a higher chance of being sold during the study period) for Gym Challenge cards compared to Base Set 2 cards. Details are provided in the text.
Table 3.
Results of univariable and multivariable Cox regression analyses.
Table 4.
Comparison of buyer demographics with respect to cumulated revenues, sales prices and latencies between offer and sale of Pokémon trading cards. In total, 220 trading cards were sold during the study period, generating a total revenue of 923.60 €.
Fig 8.
Sales distributions of Pokémon trading cards and associated revenues across the Federal Republic of Germany.
Geographic location of the 16 German federal states.
Fig 9.
Sales distributions of Pokémon trading cards and associated revenues across the Federal Republic of Germany.
Shown are the proportions of the German population per federal state.
Fig 10.
Sales distributions of Pokémon trading cards and associated revenues across the Federal Republic of Germany.
During the study period, 220 cards were sold, generating a total revenue of 923.60 €. Shown are the proportions of Pokémon trading cards sold per federal state.
Fig 11.
Sales distributions of Pokémon trading cards and associated revenues across the Federal Republic of Germany.
During the study period, 220 cards were sold, generating a total revenue of 923.60 €. Shown are the differences between the proportions of all cards sold and the proportions of the German population living in the respective federal states, expressed in percentage points.
Fig 12.
Sales distributions of Pokémon trading cards and associated revenues across the Federal Republic of Germany.
During the study period, 220 cards were sold, generating a total revenue of 923.60 €. Shown are the proportions of the total revenue per federal state.
Fig 13.
Sales distributions of Pokémon trading cards and associated revenues across the Federal Republic of Germany.
During the study period, 220 cards were sold, generating a total revenue of 923.60 €. Shown are the differences between the proportions of the total revenue and the proportions of the German population living in the respective federal states, expressed in percentage points.
Fig 14.
Artificial intelligence (AI)-supported sales price estimation of Pokémon trading cards.
The AI application Perplexity was able to calculate market price ranges for 299 out of 300 Pokémon trading cards. For one card (a Flareon 19/64 from the Jungle set), Perplexity was unable to determine a market price range. After manual reevaluation on the e-commerce platform eBay, price offers (posted prices) within, below or above Perplexity price ranges were selected at the indicated proportions.
Fig 15.
Artificial intelligence (AI)-supported sales price estimation of Pokémon trading cards.
Sales prices for 219 out of 220 Pokémon trading cards sold during the study period were compared with their initial Perplexity price ranges. Proportions of sales prices that lay within, below or above Perplexity price ranges are shown.
Fig 16.
Artificial intelligence (AI)-supported sales price estimation of Pokémon trading cards.
Sales prices for 141 out of 195 Pokémon trading cards for which the AI price range suggestions had been adopted for posted prices in the first place were compared with their Perplexity price ranges. Proportions of sales prices that lay within or below their Perplexity price ranges are displayed.
Fig 17.
Lorenz curve as graphical representation of ABC analysis.
All Pokémon trading cards sold during the study period (n = 220) were sorted in order of descending sales prices and plotted against their cumulative revenues (shown as proportions of the total revenue (100% = 923.60 €)). The initial sharp increase of the curve reflects the most expensive trading card of the sample, a Glurak (English name: Charizard) 4/102 holofoil from the Base Set, which sold for 145.00 € and alone contributed 15.7% to the total revenue. “A” cards were defined as cards with a cumulated revenue of 80% of the total revenue; “B” cards contributed the next 15% to the total revenue (i.e., from 80% to 95%), and “C” cards accounted for the remaining 5% of the total revenue (i.e., from 95% to 100%).