Inequity aversion pricing over social networks: Approximation algorithms and hardness results

We study a revenue maximization problem in the context of social networks. Namely, we generalize model introduced by Alon, Mansour, and Tennenholtz [2] that captures inequity aversion, i.e., it fact prices offered to neighboring nodes should not differ significantly. first provide approximation algorithms for natural class instances, where total is sum single-value functions. Our results improve on current state art, especially when number distinct small. This applies, instance, settings seller will only consider fixed discount types or special offers. To complement our positive results, resolve one open questions posed establishing APX-hardness problem. Surprisingly, further show NP-complete even price differences are allowed be large, as small three. Finally, extensions regarding demand type clients.