  Stackelberg Pricing Games is a two-level combinatorial pricing problem
studied in the Economics, Operation Research, and Computer Science communities.
In this paper, we consider the decade-old shortest path version of this problem
which is the first and most studied problem in this family.
  The game is played on a graph (representing a network) consisting of {\em
fixed cost} edges and {\em pricable} or {\em variable cost} edges. The fixed
cost edges already have some fixed price (representing the competitor's
prices). Our task is to choose prices for the variable cost edges. After that,
a client will buy the cheapest path from a node $s$ to a node $t$, using any
combination of fixed cost and variable cost edges. The goal is to maximize the
revenue on variable cost edges.
  In this paper, we show that the problem is hard to approximate within
$2-\epsilon$, improving the previous \APX-hardness result by Joret [to appear
in {\em Networks}]. Our technique combines the existing ideas with a new
insight into the price structure and its relation to the hardness of the
instances.
