2 research outputs found
Pricing for Collaboration Between Online Apps and Offline Venues
An increasing number of mobile applications (abbrev. apps), like Pokemon Go
and Snapchat, reward the users who physically visit some locations tagged as
POIs (places-of-interest) by the apps. We study the novel POI-based
collaboration between apps and venues (e.g., restaurants). On the one hand, an
app charges a venue and tags the venue as a POI. The POI tag motivates users to
visit the venue, which potentially increases the venue's sales. On the other
hand, the venue can invest in the app-related infrastructure, which enables
more users to use the app and further benefits the app's business. The apps'
existing POI tariffs cannot fully incentivize the venue's infrastructure
investment, and hence cannot lead to the most effective app-venue
collaboration. We design an optimal two-part tariff, which charges the venue
for becoming a POI, and subsidizes the venue every time a user interacts with
the POI. The subsidy design efficiently incentivizes the venue's infrastructure
investment, and we prove that our tariff achieves the highest app's revenue
among a general class of tariffs. Furthermore, we derive some counter-intuitive
guidelines for the POI-based collaboration. For example, a bandwidth-consuming
app should collaborate with a low-quality venue (users have low utilities when
consuming the venue's products)
Monetizing Mobile Data via Data Rewards
Most mobile network operators generate revenues by directly charging users
for data plan subscriptions. Some operators now also offer users data rewards
to incentivize them to watch mobile ads, which enables the operators to collect
payments from advertisers and create new revenue streams. In this work, we
analyze and compare two data rewarding schemes: a Subscription-Aware Rewarding
(SAR) scheme and a Subscription-Unaware Rewarding (SUR) scheme. Under the SAR
scheme, only the subscribers of the operators' data plans are eligible for the
rewards; under the SUR scheme, all users are eligible for the rewards (e.g.,
the users who do not subscribe to the data plans can still get SIM cards and
receive data rewards by watching ads). We model the interactions among an
operator, users, and advertisers by a two-stage Stackelberg game, and
characterize their equilibrium strategies under both the SAR and SUR schemes.
We show that the SAR scheme can lead to more subscriptions and a higher
operator revenue from the data market, while the SUR scheme can lead to better
ad viewership and a higher operator revenue from the ad market. We further show
that the operator's optimal choice between the two schemes is sensitive to the
users' data consumption utility function and the operator's network capacity.
We provide some counter-intuitive insights. For example, when each user has a
logarithmic utility function, the operator should apply the SUR scheme (i.e.,
reward both subscribers and non-subscribers) if and only if it has a small
network capacity