– This paper aims to focus on the problem of the optimal relocation policy for a firm that faces two types of uncertainty: one about the moments in which new (and more efficient) sites will become available; and the other regarding the degree of efficiency improvement inherent to each one of these new, yet to be known, potential location places.

Design/methodology/approach

– The paper considers the relocation issue as an optimal stopping decision problem. It uses Poisson jump processes to model the increase in the efficiency process, where these jumps occur according to a homogeneous Poisson process, but the magnitude of these jumps can have special distributions. In particular it assumes that the magnitudes can be gamma?distributed or truncated?exponential distributed.

Findings

– Particular characteristics concerning the expected optimal timing for relocation, the corresponding volatility and the value of the firm under the optimal relocation policy are derived. These results lead also to the conjecture that the optimal relocation policy is robust in terms of distributions of the degree of improvement of efficiency that are considered, as long as the expected values are the same.

Originality/value

– The paper provides an innovative approach to relocation problems, using stochastic tools. Moreover, the use of the truncated exponential and the gamma distribution functions to model the Poisson jumps is particularly suitable, given the situation under study. To the authors' knowledge, this is the first time that this type of setting is used to tackle a real options problem.

CEMAT - Center for Computational and Stochastic Mathematics