Virtual Goods Value Adjustment via Player Ratings
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Solution Overview
Problem
Existing virtual worlds lack a dynamic method to ascribe value to virtual goods, relying solely on seller-assigned values without considering player ratings or social and economic interactions within the virtual environment.
Innovation Solution
A system and method where player ratings are used to automatically adjust the value of virtual goods, incorporating factors such as the number of ratings, rater trustworthiness, and gameplay usage, to reflect their true value within the virtual economy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If seller assigns value to virtual good, then transaction simplicity is maintained, but value accuracy reflects only seller perspective without player feedback
Solution Approach 1:
The system implements a feedback mechanism where players rate virtual goods and this feedback is used to dynamically adjust the displayed value. The value calculation incorporates player ratings alongside seller-assigned values, creating a feedback loop that continuously refines the perceived value based on community input while maintaining ease of use through automated value updates.
Solution Approach 2:
The virtual good value is transformed from a static seller-assigned parameter to a dynamic value that automatically adjusts based on player ratings and community feedback. The system continuously updates values in real-time or near-real-time based on incoming ratings, making the value reflective of current player perception rather than fixed seller determination.
2Measurement precision
If player ratings are collected and processed, then value accuracy reflects community perception, but system complexity increases
Solution Approach 1:
The system automatically processes player ratings and updates values without requiring manual intervention from sellers or administrators. The automated value calculation and display updates handle the complexity internally, allowing the system to self-adjust based on community feedback while keeping the user interface simple and the operational process straightforward.
Solution Approach 2:
The system changes the parameter of value from a fixed seller-determined number to a dynamically calculated value based on multiple factors including player ratings, number of ratings received, and time elapsed. This parameter transformation allows the system to incorporate community perception automatically while managing complexity through standardized calculation rules.
3Productivity
If automated value adjustment based on ratings is implemented, then player engagement increases, but fraud and collusion risks increase
Solution Approach 1:
The system applies partial weighting to different factors in the value calculation, such as giving more weight to ratings from players with higher reputation scores or to ratings received after a certain time period. This partial action approach allows the system to engage players while incorporating safeguards against fraud by not treating all ratings equally.
Solution Approach 2:
The system introduces an intermediary evaluation layer that assesses the credibility and weight of each player rating before incorporating it into the final value calculation. This intermediary mechanism acts as a mediator between raw player feedback and the final value determination, filtering out potentially fraudulent or collusive ratings while maintaining high player engagement through transparent value adjustments.
Data Source
AI summary
A method is provided for trading virtual goods. A game environment is provided in which a first player can acquire or develop a virtual good. This virtual good has a starting value. At least one rating of the virtual good is received from a second player via the game environment. The starting value is automatically increased or decreased as a function of the at least one rating of the virtual good. The virtual good is then made available for purchase at the new value. A system for trading virtual goods is also provided.