We consider component-wise equivariant estimation of order restricted
location/scale parameters of a general bivariate distribution under quite
general conditions on underlying distributions and the loss function. This
paper unifies various results in the literature dealing with sufficient
conditions for finding improvments over arbitrary location/scale equivariant
estimators. The usefulness of these results is illustrated through various
examples. A simulation study is considered to compare risk performances of
various estimators under bivariate normal and independent gamma probability
models. A real-life data analysis is also performed to demonstrate
applicability of the derived results