  Gig economy consists of two market groups connected via an intermediary.
Popular examples are rideshares where passengers and drivers are mediated via
platforms such as Uber and Lyft. In a duopoly market, the platforms must
compete to attract not only the passengers by providing a lower rate but also
the drivers by providing better wages. While this should indicate better driver
payout, as platforms compete to attract the driver pool, real world statistics
does not indicate such. This goes completely against the intuition that the
worker side of a gig economy, given their importance, should always earn
better. We attempt to answer the low wages of drivers in the gig economy by
modeling the ridesharing game between duopoly platforms, drivers, and
passengers using Mathematical Program Networks. Our model is parsimonious,
expressive, models the same-side and cross-side externalities of the economy,
and has interpretations under both single-homing and multi-homing regimes. We
derive the conditions for the existence of a profitable duopoly and show that
it can only happen if the platforms collude together to pay the bare minimum to
the drivers. This not only answers why drivers are paid less but also provides
strong managerial insights to any interested policy maker.
