Foreign retail banner longevity

The purpose of this paper is to provide a robust examination of the factors that accelerate/decelerate the divestment timing of retail banners in international markets.

The sample represents 3,235 foreign market banner operations of 132 international retailers across 144 countries using an accelerated failure time (AFT) parametric survival modelling technique.

Banner divestment is accelerated by both weak financial performance and smaller size. Furthermore, there is a synergistic negative detriment to the combination of both factors on divestment. Banner divestment is decelerated by deploying the corporation’s dominant format in the home country. Moreover, inadequately performing dominant banners are allowed more time to turn around their operations than subpar non-dominant banners. Concurrently, when host country markets are growing, poorly performing dominant banners are given more time to improve performance. When home market performance weakens, smaller, poorly performing banner divestment is accelerated.

The large data set covers more than half of the world so the authors are limited to observing corporate divestments without the benefit of the managerial decision-making process. The authors only have access to divestment data in annual units, which limits the ability to provide precise timing information. Though the authors have a wide variation in country conditions, data on smaller, poorer countries and domestic competitors is limited.

Small, poorly performing retail chains in foreign markets are divested faster than their counterparts. When retailers internationalize with their dominant chains, management tends to give these banners more time to succeed than non-dominant counterparts. Evidence also suggests that managers hesitate to withdrawal from a foreign market when the dominant banner is involved, regardless of a chain’s stunted growth and subpar performance.

This study provides the first examination of factors driving the divestment times of international retail chains using rigorous empirical survival time methodologies.