  Facility location decisions significantly impact customer behavior and
consequently the resulting demand in a wide range of businesses. Furthermore,
sequentially realized uncertain demand enforces strategically determining
locations under partial information. To address these issues, we study a
facility location problem where the distribution of customer demand is
dependent on location decisions. We represent moment information of stochastic
demand as a piecewise linear function of facility-location decisions. Then, we
propose a decision-dependent distributionally robust optimization model, and
develop its exact mixed-integer linear programming reformulation. We further
derive valid inequalities to strengthen the formulation. We conduct an
extensive computational study, in which we compare our model with the existing
(decision-independent) stochastic and robust models. Our results demonstrate
superior performance of the proposed approach with remarkable improvement in
profit and quality of service by extensively testing problem characteristics,
in addition to computational speed-ups due to the formulation enhancements.
These results draw attention to the need of considering the impact of location
decisions on customer demand within this strategic-level planning problem.
